SEARCH · Search NASA

Results for “event driven”

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.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 397 records · Page 22

All sources NASA NTRS DOE OSTI

DOE OSTI2023

DUNE-PRISM – A New Method to Measure Neutrino Oscillations

The Deep Underground Neutrino Experiment (DUNE) is a next-generation long baseline neutrino oscillation experiment designed to make precision measurements in a 1.2 2.4 MW neutrino beam, which is directed 1285 km from the Fermi National Accelerator Laboratory (Fermilab) to the Sandford Underground Research Facility (SURF) in South Dakota. Neutrinos are measured at two detector facilities: a near detector located at Fermilab close where the beam is produced and a far detector at SURF. The neutrino beam can be configured to be composed primarily of either muon or anti-muon neutrinos. DUNE measures the disappearance of muon and anti-muon neutrinos and appearance electron and anti-electron neutrinos in the neutrino beam. Measuring these neutrino flavour transitions provides DUNE with sensitivity to the neutrino mass ordering, $\delta_{CP}$, $\theta_{13}$, $\theta_{23}$ and the magnitude of $\Delta m^2_{23}$. The DUNE Precision Reaction Independent Spectrum Measurement (DUNE-PRISM) concept presents a novel way to perform a neutrino oscillation analysis, which has the potential to significantly reduce the impact of large systematic uncertainties in the neutrino interaction model. The PRISM method linearly combines measurements of off-axis neutrino interactions at the DUNE near detector to produce data-driven predictions of the oscillated neutrino event rate spectrum at the far detector. By building an oscillated far detector prediction directly from data, any unknown or poorly modelled neutrino interaction effects will be naturally incorporated into the measurement of the parameters of the neutrino oscillation model. This thesis presents the first complete neutrino oscillation analysis for DUNE using the PRISM method. Details of the methodology are fully explained and the prospects for further improvements to the techniques described are highlighted. The expected impact and relative importance of the neutrino flux, cross section and detector systematic uncertainties are described in detail. Finally, this thesis demonstrates that the PRISM method is capable of performing a measurement of the oscillation parameters that is robust against neutrino interaction modelling errors.

Hasnip, Ciaran↗

NASA NTRS2011

Intensity Variation of Solar Energetic Particle Events

This paper updates the influence of environmental and source factors of shocks driven by corona) mass ejections (CMEs) that are likely to influence the intensity of solar energetic particle (SEP) events. The intensity variation due to CME interaction reported in Gopalswamy et al. (2004, JGR 109, Al2105) is confirmed by expanding the investigation to all the large SEP events of solar cycle 23. The large SEP events are separated into two groups, one associated with CMEs running into other CMEs, and the other with CMEs running into the ambient solar wind. SEP events with CME interaction generally have a higher intensity. New possibilities such as the influence of corona) holes on the SEP intensity are also discussed. For example, the presence of a large coronal hole between a well-connected eruption and the solar disk center may render the shock poorly connected because of the interaction between the CME and the coronal hole. This point is illustrated using the 2004 December 3 SEP event delayed by about 12 hours from the onset of the associated CME. There is no other event at the Sun that can be associated with the SEP onset. This event is consistent with the possibility that the coronal hole interaction influences the connectivity of the CMEs that produce SEPs, and hence the intensity of the SEP event.

Gopalswamy, Nat↗

DOE OSTI2025

Weather-Driven Resilience for Distribution Systems

With increasing billion dollar disasters due to weather events, it is of utmost priority for utility and grid operators to maintain and enhance the resilience of distribution grid. Traditionally, such analysis were conducted with reliability metrics alone. However, with increasing complexity of distribution grid and advancements in grid edge resources, evaluating grid resilience is challenging and involves multi-faceted analysis of the impact of weather events on the distribution grid. This presentation provides background, details, and future works in the field of weather-driven resilience for power distribution systems.

24 POWER TRANSMISSION AND DISTRIBUTION↗

NASA NTRS2012

Energy Spectra, Composition, and Other Properties of Ground-Level Events During Solar Cycle 23

We report spacecraft measurements of the energy spectra of solar protons and other solar energetic particle properties during the 16 Ground Level Events (GLEs) of Solar Cycle 23. The measurements were made by eight instruments on the ACE, GOES, SAMPBX, and STEREO spacecraft and extend from approximately 0.1 to approximately 500-700 MeV. All of the proton spectra exhibit spectral breaks at energies ranging from approximately 2 to approximately 46 MeV and all are well fit by a double power-law shape. A comparison of GLE events with a larger sample of other solar energetic particle (SEP) events shows that the typical spectral indices are harder in GLE events, with a mean slope of -3.18 at greater than 40 MeV/nuc. In the energy range 45 to 80 MeV/nucleon about approximately 50% of GLE events have properties in common with impulsive He-3-rich SEP events, including enrichments in Ne/O, Fe/O, Ne-22/Ne-20, and elevated mean charge states of Fe. These He-3 rich events contribute to the seed population accelerated by CME-driven shocks. An analysis is presented of whether highly-ionized Fe ions observed in five events could be due to electron stripping during shock acceleration in the low corona. Making use of stripping calculations by others and a coronal density model, we can account for events with mean Fe charge states of (Q(sub Fe) is approximately equal to +20 if the acceleration starts at approximately 1.24-1.6 solar radii, consistent with recent comparisons of CME trajectories and type-II radio bursts. In addition, we suggest that gradual stripping of remnant ions from earlier large SEP events may also contribute a highly-ionized suprathermal seed population. We also discuss how observed SEP spectral slopes relate to the energetics of particle acceleration in GLE and other large SEP events.

Mewaldt, R. A.↗

NASA NTRSDate not supplied

Large Scale Volcanism: An Explanation for the Heat-death of Venus-like Worlds

Large scale volcanism has played a critical role in the long-term habitability of Earth and possibly Venus. Large Igneous Provinces (LIPs) are in fact the cause of most major extinction events in Earth’s history, contrary to the popular belief about the devastation from large bolides. We examine the timing of Large Igneous Provinces (LIPs) through Earth’s history [1] to estimate the likelihood of nearly simultaneous events that could drive a planet into an extreme moist or runaway greenhouse, quenching subductive plate tectonics. Such events would end volatile cycling and may have driven Venus from a cool temperate state into the heat-death we see today. Using the Earth's LIP record [1] we have found that LIP events are distributed randomly throughout the past 3 billion years. A conservative estimate of the rate of LIPs in a random history statistically the same as Earth’s, pairs and triplets of LIPs closer in time than 0.1-1 million years are likely. This simultaneity threshold is significant to the extent that it is less than the time over which environmental effects have been shown to persist, for example in the Siberian Traps record [2,3]. With the recent mission selections of VERITAS and EnVision it may be possible for their high resolution radar maps to distinguish LIPs in the surface record we can see today on Venus.

Large Igneous Provinces↗

NASA NTRS1999

Evidence for Directly Driven Auroral Signatures Resulting from Interplanetary Pressure Pulses

It has been observed that the auroral signature of the arrival of an interplanetary pressure pulse at the bow shock causes an initial brightening near noon. Consequently, the bright region propagates to the night side via the dawn and dusk flanks. The delay time for subsequent auroral breakup is observed to vary significantly from seconds to hours. We have examined the 1998 and early 1999 interplanetary pressure pulse events recorded by WIND and ACE (over 35 in all) and correlated these with the Polar UVI data for the events that are imaged. Evidence for directly driven auroral activity resulting from an interplanetary pressure pulse will be discussed as well as the variation of the delay time for auroral breakup.

Spann, J. F., Jr.↗

DOE OSTI2022

Subsurface stress criticality associated with fluid injection and determined using machine learning

Machine-learning methods and apparatus are disclosed to determine critical state or other parameters related to fluid-driven failure of a terrestrial locale impacted by anthropogenic activities such as hydraulic fracturing, hydrocarbon extraction, wastewater disposal, or geothermal harvesting. Acoustic emission, seismic waves, or other detectable indicators of microscopic processes are sensed. A classifier is trained using time series of microscopic data along with corresponding data of critical state or failure events. In disclosed examples, random forests and artificial neural networks are used, and grid-search or EGO procedures are used for hyperparameter tuning. Once trained, the classifier can be applied to live data from a fluid injection locale in order to assess a frictional state, assess seismic hazard, assess permeability, make predictions regarding a future fluid-driven failure event, or drive engineering solutions for mitigation or remediation. Variations are disclosed.

Johnson, Paul Allan↗

DOE OSTI2026

Envelope-driven comfort risk in residential demand response

Residential demand response (DR) is a valuable resource for grid reliability, but remains challenging because the highly heterogeneous residential building stock leads to widely varying and hard-to-predict load and comfort responses during DR events. Although prior research has estimated the technical potential of DR-capable technologies for achieving energy demand savings, little is known about how they affect thermal comfort. In particular, it remains unclear how indoor thermal conditions due to DR depend on the thermal envelope characteristics of the housing stock. To address this gap, this study provides a systematic, location-specific assessment of indoor thermal performance during DR-events across the US housing stock using both typical DR weather data and detailed building metadata. We evaluate how envelope characteristics influence indoor temperatures during realistic simulated summer and winter DR events across 37 US locations, applying both temperature threshold and rate of temperature change criteria to estimate region-level probabilities of discomfort. Additionally, we show the impact of distinct weather patterns that intensify or abate thermal stress on comfort outcomes. Results show a near-universal overheating risk in summer DR events, where comfort outcomes are strongly influenced by rapid risk of comfort violations. In contrast, overall winter DR discomfort risk is lower, risk escalation is more gradual and shows greater sensitivity to event duration. These findings offer a data-driven quantification of comfort risk across diverse climates and building envelopes, demonstrating the need for region-specific DR scheduling and discomfort mitigation strategies tailored to local weather patterns and the performance of existing residential buildings.

Demand response↗

NASA NTRS1984

Observations of Gulf Stream-induced and wind-driven upwelling in the Georgia Bight using ocean color and infrared imagery

Ocean color and infrared imagery from U2 aircraft and satellite sensors are used to study upwelling interaction between Gulf Stream and continental shelf waters in the Georgia Bight. The photographic data are combined with in situ measurements of currents, chlorophyll, temperature, salinity, coastal winds, and sea-level in observations of five different upwelling events including a near-short wind-driven upwelling caused by topographic effects, three filament-induced upwellings in the Gulf Stream, and a possible meander-induced upwelling event in the Gulf Stream. Chlorophyll distributions are used to trace the circulation and propagation of filaments along the advective routes by which the water moves offshore. Photographic and mooring array measurements of temperature time series are found to provide nearly identical results for the phase speeds of each event. Field measurements of surface pigments, and Nimbus/7 coastal zone color scanner (CZCS) estimates are found to agree well over the range of concentrations 0.1 to 0.7 mg/m to the third. Examples of U2/Ocean Color Scanner and Nimbus 7 CZCS photographs are provided.

Mcclain, C. R.↗

DOE OSTI2021

Search for phenomena beyond the Standard Model in events with large $b$-jet multiplicity using the ATLAS detector at the LHC

A search is presented for new phenomena in events characterised by high jet multiplicity, no leptons (electrons or muons), and four or more jets originating from the fragmentation of b -quarks ( b -jets). The search uses 139 fb -1 of $\sqrt{s}$ = 13 TeV proton–proton collision data collected by the ATLAS experiment at the Large Hadron Collider during Run 2. The dominant Standard Model background originates from multijet production and is estimated using a data-driven technique based on an extrapolation from events with low b -jet multiplicity to the high b -jet multiplicities used in the search. No significant excess over the Standard Model expectation is observed and 95% confidence-level limits that constrain simplified models of R-parity-violating supersymmetry are determined. The exclusion limits reach 950 GeV in top-squark mass in the models considered.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2023

Bayesian High-Rank Hankel Matrix Completion for Nonlinear Synchrophasor Data Recovery

Phasor measurement units (PMUs) provide high temporal-resolution synchrophasor measurements for power system monitoring and control. The frequent data quality issues, such as missing and bad data, prevent the incorporation of synchrophasor data in real-time operations. Most existing data-driven data recovery methods assume the power system dynamics can be approximated by a linear dynamical system, and the recovery performance degrades significantly when the power system is experiencing nonlinear dynamics during significant events. Here, this paper proposes a data-driven Bayesian nonlinear synchrophasor data recovery method (Ba-NSDR) that can recover a consecutive time period of simultaneous data losses or errors across all channels, even when the underlying system is highly nonlinear. The idea is to lift the Hankel matrix of the spatial-temporal synchrophasor data to a higher dimension such that the lifted Hankel matrix is low-rank in that space and can be processed with the kernel trick. Our proposed Bayesian method then infers the probabilistic distributions of synchrophasor from the partial observations. Some distinctive features of Ba-NSDR include an uncertainty index to measure the accuracy of the recovery result and the robustness to parameter selections. Our method is verified on both synthetic and recorded event datasets.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2024

Simulated nitrogen deposition and precipitation events alter microbial carbon cycling during early stages of litter decomposition

Plant litter decomposition is a major nutrient input to terrestrial ecosystems that is primarily driven by microorganisms. Litter quality is considered a key drive of decomposition; however, human-induced global disturbance like nitrogen deposition and increasing extreme precipitation events will shift nutrient availability during litter decomposition. Little is known about how shifting nutrient availability will impact dissolved organic matter concentrations and microbially driven carbon cycling that are critical to soil organic matter formation. This study investigated the effect of simulated nitrogen deposition and repeated precipitation events on microbially driven carbon flow during short-term litter decomposition using a ‘common garden’ experiment with microcosms containing sand and blue grama grass litter inoculated with different microbial communities. Overall, nitrogen deposition decoupled respiration and dissolved organic carbon (DOC) by increasing respiration and not affecting DOC concentrations. Moreover, nitrogen deposition had no effect on microbial carbon use efficiency (CUE). Repeated simulated precipitation events significantly increased DOC concentrations, decreased microbial CUE, increased the microbial metabolic quotient (qCO2), and altered microbial composition and diversity. These findings highlight the complex interactions and responses of surface litter decomposers to shifting nutrient availability and contradicts previous findings that nitrogen deposition will increase soil carbon sequestration from a larger supply of DOC and reduced respiration.

59 BASIC BIOLOGICAL SCIENCES↗

NASA NTRS1992

Particle acceleration in solar flares - Observations

Contrary to our historical understanding, the energetic particles in most major solar proton events do not come from the flare itself. The particle abundances, ionization states, time evolution, and longitude distributions all indicate that the particles are accelerated from the ambient plasma by a shock wave driven by a coronal mass ejection in these events. In contrast, the particles that do come from impulsive solar flares are unique in character. These particles are electron rich, have He-3/He-4 enhancements of up to 10,000, and enhancements in heavy elements such as Fe/C by factors of 10. The high ionization state of Fe, +20 indicates that the material has been heated to temperatures of about 2 x 10 exp 7 K. It is generally believed that preferential heating by selective absorption of plasma waves is combined with stochastic acceleration in these events. Recent studies of the broad gamma-ray lines emitted by energetic particles within the flare loops indicate that they are also Fe-rich, He-3 rich and proton-poor like the particles seen at 1 AU. In large impulsive events, particles from the impulsive phase may be reaccelerated by a coronal blast-wave shock.

Reames, Donald V.↗

DOE OSTI2025

Techno-Economic Analysis of Data-Driven and Transactive Approaches for Resilience Enhancement

As extreme weather events lead to more frequent power outages, understanding and enhancing grid resilience is critical to mitigating economic losses and non-energy impacts from service disruptions. Here, this study introduces a novel techno-economic analysis framework for evaluating resilience enhancement mechanisms. The framework combines grid response modeling with a co-simulation approach and valuation methodology to provide a comprehensive assessment. We apply this framework to a realistic case study of the Texas grid during Winter Storm Uri in February 2021. Two advanced resilience strategies are analyzed: a data-driven rolling outage mechanism and a transactive energy (TE) based allocation scheme. The rolling outage scheme selectively serves customers based on real-time curtailment needs, while the TE scheme allows customers to trade energy allocations according to their preferences. Our findings show that both the rolling outage and TE schemes significantly outperform conventional methods (i.e. controlled outages) by reducing the amount of energy not supplied to customers by 41% and 64%, respectively. These approaches also enhance flexibility and customer satisfaction, while improving energy utilization for greater resilience. Additionally, they maintain thermal comfort about 3.5 times better and substantially lower customer risk exposure. A key contribution of this study is addressing both utility and customer perspectives while considering both energy and non-energy impacts. The techno-economic analysis indicates that implementing these resilience enhancement strategies would incur an additional 1.1Bto1.6B in utility costs but has the potential to avoid 17.3Bto18B of customer losses as compared to existing solutions, thereby underscoring the value of investing in advanced resilience, as it provides significant societal benefits to customers.

42 ENGINEERING↗

NASA NTRS1999

The Role of Self-Organized Criticality in the Substorm Phenomenon and its Relation to Localized Reconnection in the Magnetospheric Plasma Sheet

Evidence is presented that suggests there is a significant self-organized criticality (SOC) component in the dynamics of substorms in the magnetosphere. Observations of BBFs, fast flows, localized dipolarizations, plasma turbulence, etc. are taken to show that multiple localized reconnection sites provide the basic avalanche phenomenon in the establishment of SOC in the plasma sheet. First results are presented from a continuing plasma physical study of this avalanche process. A one-dimensional resistive MHD model of a magnetic field reversal is discussed. Resistivity, in this model, is self-consistently generated in response to the excitation of an idealized current-driven instability. When forced by convection of magnetic flux into the field reversal region, the model yields rapid magnetic field annihilation through a dynamic behavior that is shown to exhibit many of the characteristics of SOC. Over a large range of forcing strengths, the annihilation rate is shown to self-adjust to balance the rate at which flux is convected into the reversal region. Several analogies to magnetotail dynamics are discussed: (1) It is shown that the presence of a localized criticality in the model produces a remarkable stability in the global configuration of the field reversal while simultaneously exciting extraordinarily dynamic internal evolution. (2) Under steady forcing, it is shown that a loading-unloading cycle may arise that, as a consequence of the global stability, is quasi-periodic and, therefore, predictable despite the presence of internal turbulence in the field distribution. Indeed, it is shown that the global loading-unloading cycle is a consequence of the internal turbulence. (3) It is shown that, under steady, strong forcing the loading-unloading cycle vanishes. Instead, a recovery from a single unloading persists indefinitely. The field reversal is globally very steady while internally it is very dynamic as field annihilation goes on at the rate necessary to match the strong forcing. From this result we speculate that steady magnetospheric convection events result when the plasma sheet has been driven close to criticality over an extended spatial domain. During these events, we would expect to find localized reconnection sites distributed over the spatial domain of near criticality and we would expect to find plasma sheet transport in that domain to be closely related to that of BBF and fast flow events.

Klimas, Alex J.↗

NASA NTRSDate not supplied

A Knowledge Graph Framework for Organizing Heterogeneous Datasets for Utilization in Classical and Quantum Computing: Current Challenges and Future Directions

"The escalating impact of climate change induced extreme weather events in urban, suburban, and rural environments demands a rethink of how we have been using the single event-based or use-case-based knowledge graph models. The lack of representation in interaction within environmental variables found in literature led to the development of a novel framework that reflects the true nature of the interconnectedness in our environment. We propose an Environmental Interaction Knowledge Graph (EIKG) framework. This general EIKG framework works as the basis for interconnected environmental events by knitting interrelated events such as hurricanes leading to storm surges, which lead to flood events that could cause mudslides, landslides, etc., The cascading nature of one event leading to another related event in the environment requires an adequate understanding of each event using contextual information before conducting any data-driven analytics. This vision paper showcases how the EIKG:floods, EIKG:wildfire EIKG:landslides, etc, can be derived from a base case framework of EIKG as those individual events are interconnected with some common denominator variables. As an example, the precipitation variable is used in the flood case study as well as in the wildfire case study, as excessive precipitation levels lead to floods, and lack of precipitation leads to droughts and wildfires. We identify the precipitation variable as a “common-denominator-variable” in extreme weather events that play a key role in modeling the environment leading to different extreme weather events based on the variability of that variable (varying values where low precipitation leads to drought, and high values lead to floods). We use the insights gained from EIKG to conduct classical and Quantum Machine Learning (QML) based data analysis on the research questions developed. Our preliminary study shows how the Variational Quantum Classifier (VQC) and Quantum Support Vector Classifier (QSVC) are used along with the classical machine learning models to compare the model accuracies. Our study elaborates on how a quantitative analysis uses state-of-the-art machine learning techniques that include implementing both classical and quantum machine learning models and developing the knowledge graph. The EIKG is used to organize heterogeneous datasets and integrate the relations to case-specific extreme weather events such as floods. The study uses datasets such as county-to-country residential mobility data, socioeconomic datasets from the US Census Bureau, climate and weather-related Earth Observational data from NASA, and critical infrastructure data from the Homeland Infrastructure datasets."

Knowledge Graphs, Quantum Computing, Heterogenous ↗

NASA NTRS2008

Ion Anisotropy and High-Energy Variability of Large Solar Particle Events: A Comparative Study

We have made comparative studies of ion anisotropy and high-energy variability of solar energetic particle (SEP) events previously examined by the Solar, Heliospheric, and Interplanetary Environment (SHINE) Workshop campaign. We have found distinctly different characteristics of SEPs between two large "gradual" events having very similar solar progenitors (the 2002 April 21 and August 24 events). Since the scattering centers of SEPs are approximately frozen in the solar wind, we emphasize work in the solar-wind frame where SEPs tend to be isotropized, and small anisotropies are easier to detect. While in the August event no streaming reversal occurred, in the April event the field-aligned anisotropy of all heavy ions showed sign of streaming reversal. The difference in streaming reversal was consistent with the difference in the presence of the outer reflecting boundary. In the April event the magnetic mirror, which was located behind the interplanetary shock driven by the preceding coronal mass ejection (CME), could block the stream of SEPs, while in the August event SEPs escaped freely because of the absence of nearby boundary. The magnetic mirror was formed at the bottleneck of magnetic field lines draped around a flank of the preceding CME. In the previous SHINE event analysis the contrasting event durations and Fe/O ratios of the both events were explained as the interplay between shock geometry and seed population. Our new findings, however, indicate that event duration and time as well as spectral variation are also affected by the presence of a nearby reflecting boundary.

Tan, Lun C.↗

DOE OSTI2026

Exploring Wildfire & Energy data toward State Prioritization Index (WESPI)

Energy infrastructure can both induce and suffer risks from wildfires ranging from direct damage to energy assets such as substations and power lines to Public Safety Power Shutoffs. Recent wildfire events underscore the need for data-driven approaches that help states and utilities proactively plan for wildfire risk. Existing national tools such as Federal Emergency Management Agency (FEMA)’s National Risk Index (NRI) are valuable for community hazard planning. However, they are less suited for energy infrastructure, as they emphasize population and building exposure rather than system vulnerabilities. In this paper, we explore relationships between energy and wildfire data and present a Wildfire-Energy State Prioritization Index (WESPI). Our methodology combines data from the US Forest Service’s Fire Simulation (FSIM) dataset with energy resilience metrics, historical fire incidents, and geospatial data on transmission lines and fire stations. Correlation analyses suggest that FSIM burn probability is more strongly associated with power outage metrics (ρ = 0.32) than NRI wildfire frequency, and counties with a greater density of fire stations experience more frequent, but less intense wildfires. We further leverage data for burn probability, transmission line density, and fire station density to develop a Wildfire-Energy State Prioritization Index (WESPI) to highlight counties where wildfire hazard, infrastructure exposure, and limited suppression capacity converge. The index provides a consistent, scalable framework for state energy offices and utilities to screen counties for vegetation management, optimization of outage management system deployment, and to inform wildfire mitigation plans.

Critical infrastructure↗