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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 541 records · Page 30
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Data-driven model validation for neutrino-nucleus cross section measurements

Neutrino-nucleus cross section measurements are needed to improve interaction modeling to meet the precision needs of neutrino experiments in efforts to measure oscillation parameters and search for physics beyond the Standard Model. We review the difficulties associated with modeling neutrino-nucleus interactions that lead to a dependence on event generators in oscillation analyses and cross section measurements alike. We then describe data-driven model validation techniques intended to address this model dependence. The method relies on utilizing various goodness-of-fit tests and the correlations between different observables and channels to probe the model for defects in the phase space relevant for the desired analysis. These techniques shed light on relevant mismodeling, allowing it to be detected before it begins to bias the cross section results. We compare more commonly used model validation methods which directly validate the model against alternative ones to these data-driven techniques and show their efficacy with fake data studies. These studies demonstrate that employing data-driven model validation in cross section measurements represents a reliable strategy to produce robust results that will stimulate the desired improvements to interaction modeling.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Characterizing climate pathways using feature importance on echo state networks

The 2022 National Defense Strategy of the United States listed climate change as a serious threat to national security. Climate intervention methods, such as stratospheric aerosol injection, have been proposed as mitigation strategies, but the downstream effects of such actions on a complex climate system are not well understood. The development of algorithmic techniques for quantifying relationships between source and impact variables related to a climate event (i.e., a climate pathway) would help inform policy decisions. Data-driven deep learning models have become powerful tools for modeling highly nonlinear relationships and may provide a route to characterize climate variable relationships. In this paper, we explore the use of an echo state network (ESN) for characterizing climate pathways. ESNs are a computationally efficient neural network variation designed for temporal data, and recent work proposes ESNs as a useful tool for forecasting spatiotemporal climate data. However, ESNs are noninterpretable black-box models along with other neural networks. The lack of model transparency poses a hurdle for understanding variable relationships. We address this issue by developing feature importance methods for ESNs in the context of spatiotemporal data to quantify variable relationships captured by the model. We conduct a simulation study to assess and compare the feature importance techniques, and we demonstrate the approach on reanalysis climate data. In the climate application, we consider a time period that includes the 1991 volcanic eruption of Mount Pinatubo. This event was a significant stratospheric aerosol injection, which acts as a proxy for an anthropogenic stratospheric aerosol injection. Furthermore, we are able to use the proposed approach to characterize relationships between pathway variables associated with this event that agree with relationships previously identified by climate scientists.

black-box models↗
NASA NTRS2010

THEMIS Observations of Directly-Driven Pi2 Pulsations

The THEMIS tail seasons have provided an unprecedented opportunity to examine the causal relationship between midtail plasma flows and low latitude Pi2 pulsations. We present several events where multiple THEMIS spacecraft observed magnetotail flow bursts which were followed up to several minutes later by ground Pi2 pulsations. We find good agreement with the waveforms of the flow bursts and flank Pi2, in agreement with the hypothesis that Pi2 at low-latitude on the flank are directly-driven by periodic variations in the flow bursts. For at least I event we are able to follow the Pi2 impulses from the periodic flow bursts on the nightside. to ground Pi2 at the flanks, and finally through the dayside magnetosphere as observed by GOES. We further place the physical mechanism generating these Pi2 into the context of sub storm onset. We conclude by discussing the sequence and coupling of events that are necessary to explain the correlation, and the constraints this places on models of transient magnetospheric transport.

Kepko, L.↗
DOE OSTI2024

Data-driven Modeling for Grid Edge IBRs: A Digital Twin Perspective of User-Defined Models

Recent events in Odessa have brought attention to the challenges associated with the interaction between Inverter- Based Resources (IBRs) and the transmission and distribution system. The NERC event diagnosis report has highlighted sev- eral issues, emphasizing the need for continuous performance monitoring of these IBRs by system operators. Key areas of concern include the mismatch of control and protection perfor- mance of IBRs between the original equipment manufacturer (OEM)-provided models and field measurements. The inability to replicate the realistic response can result in incorrect reliability and resilience studies. In this paper, we developed an approach on how to emulate the behavior of an IBR using measurement data obtained for system operators to utilize in real-time and long- term planning. Two experiments are conducted in the phasor domain and electromagnetic transients (EMT) domain to emulate the behavior for grid forming and grid following inverters under various operating conditions and the effectiveness of the proposed model is demonstrated in terms of accuracy and ease of utilizing user-defined models (UDMs)

Mahapatra, Kaveri [BATTELLE (PACIFIC NW LAB)]↗
DOE OSTI2025

How Flood Hazards in a Warming Climate Could Be Amplified by Changes in Spatiotemporal Patterns and Mechanisms of Water Available for Runoff

Prior research on climate change impacts on flooding has primarily focused on changes in extreme rainfall magnitudes, often neglecting snow processes and spatiotemporal storm patterns, such as hyetograph shapes and areal reduction factors (ARFs). This study examines projected changes in extreme water available for runoff (W) events in two snow-dominated basins in the western United States: the Yakima River Basin (YRB) in Washington State and the Walker River Basin (WRB) spanning the California-Nevada border. We analyze changes in W magnitudes, mechanisms, hyetograph shapes, and ARFs, and study their compounded impacts on flood hazard. Our findings suggest increased extreme W magnitudes across a large portion of the basins, with steeper or flatter hyetographs, and higher ARF values under the future climate. These changes are driven by a shift from seasonal snowmelt to more rain-on-snow events at higher elevations and by increased rainfall at lower elevations. We then use a single event-based rainfall-runoff model to estimate flood hazard changes based on extreme W magnitudes, hyetograph shapes, ARFs, and their compounded impacts. Our analysis reveals that focusing solely on the magnitude of changes in extreme W can significantly underestimate future flood hazards and uncertainties. Ignoring future changes in spatiotemporal patterns can underestimate future flood hazards by 63% and underestimate the uncertainty in future flood events by 18% in the WRB. These results underscore the necessity of incorporating spatiotemporal dynamics into future flood hazard assessments to provide a more accurate evaluation of potential impacts.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2018

An Overview of Science Challenges Pertaining to our Understanding of Extreme Geomagnetically Induced Currents

Vulnerability of man-made infrastructure to Earth-directed space weather events is a serious concern for today's technology-dependent society. Space weather-driven geomagnetically induced currents (GICs) can disrupt operation of extended electrically conducting technological systems. The threat of adverse impacts on critical technological infrastructure, like power grids, oil and gas pipelines, and communication networks, has sparked renewed interest in extreme space weather. Because extreme space weather events have low occurrence rate but potentially high impact, this presents a major challenge for our understanding of extreme GIC activity. In this chapter, we discuss some of the key science challenges pertaining to our understanding of extreme events. In addition, we present an overview of GICs including highlights of severe impacts over the last 80 years and recent U.S. Federal actions relevant to this community.

Ngwira, Chigomezyo M.↗
NASA NTRS2001

The Effect of Solar Proton Events on Ozone and Other Constituents in the Middle Atmosphere

Solar proton events (SPEs) can result in increases in both HO(x) (H, OH, HO2) and NO(x) (N, NO, NO2) constituents in the middle atmosphere polar region (>60 degrees geomagnetic). FlO(x) constituents produced by SPEs caused decreases in mesospheric and upper stratospheric ozone observed during several events. Recent SPEs in July and November of 2000 caused ozone decreases of over 30 percent during the event as measured by UARS HALOE and NOAA 14 SBUV/2. These HO(x)-driven ozone depletions last only during the SPEs (several hours to a few days) because of the short lifetimes of HO(x) constituents in the atmosphere. The NO(x) species feed into the entire odd nitrogen family NO(y) (N, NO, NO2, NO3, N2O5, HNO,14NO4, CIONO2, BrONO2) over a period of hours to weeks. The NO(y) family lasts several months or more in the stratosphere with low sun conditions. The two largest SPEs in the past 30 years, October 1989 and August 1972, caused polar stratospheric ozone depletions >10 percent for weeks past the events. The SPE in July 2000, third largest in 30 years, was measured by NOAA 14 SBUV/2 to decrease ozone by several percent for days past the event. Enhancements in mesospheric NO(x) of over 50 ppbv were also measured by UARS HALOE during this event. A review of the influence of SPEs on ozone and other constituents in the middle atmosphere will be given in this talk.

Jackman, Charles H.↗
DOE OSTI2020

Hypothetical Efficiency of Electrical to Mechanical Energy Transfer during Individual Stochastic Molecular Switching Events

There are now many examples of single molecule rotors, motors and switches in the literature that, when driven by photons, electrons or chemical reactions, exhibit well defined motions. As a step towards using these single molecule devices to perform useful functions one must understand how they interact with their environment and quantify their ability to perform work on it. Using a single molecule rotary switch we examine the transfer of electrical energy, delivered via electron tunneling, to mechanical motion and measure the forces the switch experiences with a non-contact q-plus atomic force microscope. Action spectra reveal that the molecular switch has two stable states and can be excited resonantly between them at a bias of 100 mV via a one-electron inelastic tunneling process which corresponds to an energy input of 16 zepto Joules. Furthermore, while the electrically induced switching events are stochastic and no net work is to done on the cantilever, by measuring the forces between the molecular switch and the AFM cantilever we can derive the maximum hypothetical work the switch could perform during a single switching event which is ~55 meV, equal to 8.9 zepto Joules which translates to a hypothetical efficiency ~55% per individual inelastic tunneling electron induced switching event. When co considering the total electrical energy input this drops to 1x10 -7 % due to elastic tunneling events that dominate the tunneling current. However, this approach constitutes a general method for quantifying and comparing the energy input and output of molecularmechanical devices.

36 MATERIALS SCIENCE↗
NASA NTRS2009

Observation and Interpretation of Energetic Neutral Hydrogen Atoms from the December 5, 2006 Solar Event

We report the first observations of energetic neutral atoms (ENAs) from a solar flare/coronal mass ejection event. The observations were made during the December 5, 2006 X9 solar flare, located at E79, by the Low Energy Telescopes (LETs) on the STEREO A and B spacecraft. Within 1-2 hours of the flare onset, both LETs observed a sudden burst of 1.6 to 15 MeV protons arriving hours before the onset of the main solar energetic particle (SEP) event at Earth. More than 70% of these particles arrived from a longitude within +-10 degrees of the Sun. The derived emission profile at the Sun lasted for more than an hour and had a profile remarkably similar to the GOES soft X-ray profile. The observed arrival directions and energy spectrum argue strongly that the particle events <5 MeV were due to energetic neutral hydrogen atoms that were stripped of their electrons upon entering the LET sensor. To our knowledge, this is the first reported observation of ENA emission from a solar flare/coronal mass ejection. We discuss possible origins for the production of ENAs in solar events, including charge-transfer reactions involving both flare and shock-accelerated protons. Assuming isotropic emission, we find that ~2 x 10E28 ENAs escaped from the Sun in the upper hemisphere. Based on the 2.2 MeV gamma-ray emission observed by RHESSI in this event, and using measured and theoretical cross sections, we estimate that ~3 x 10E31 ENAs with 1.8 - 5 MeV could be produced by protons accelerated in the flare. CME-driven shock acceleration is also a possible ENA source, but unfortunately there were no CME observations available from this event. Taking into account ENA losses, we conclude that the observed ENAs were most likely produced in the high corona at heliocentric distances 1.6 solar radii.

Mewaldt, R. A.↗
NASA NTRS2020

Application of Sparse Identification of Nonlinear Dynamics for Physics-Informed Learning

Advances in machine learning and deep neural networks has enabled complex engineering tasks like image recognition, anomaly detection, regression, and multi-objective optimization, to name but a few. The complexity of the algorithm architecture, e.g., the number of hidden layers in a deep neural network, typically grows with the complexity of the problems they are required to solve, leaving little room for interpreting (or explaining) the path that results in a specific solution. This drawback is particularly relevant for autonomous aerospace and aviation systems, where certifications require a complete understanding of the algorithm behavior in all possible scenarios. Including physics knowledge in such data-driven tools may improve the interpretability of the algorithms, thus enhancing model validation against events with low probability but relevant for system certification. Such events include, for example, spacecraft or aircraft sub-system failures, for which data may not be available in the training phase. This paper investigates a recent physics-informed learning algorithm for identification of system dynamics, and shows how the governing equations of a system can be extracted from data using sparse regression. The learned relationships can be utilized as a surrogate model which, unlike typical data-driven surrogate models, relies on the learned underlying dynamics of the system rather than large number of fitting parameters. The work shows that the algorithm can reconstruct the differential equations underlying the observed dynamics using a single trajectory when no uncertainty is involved. However, the training set size must increase when dealing with stochastic systems, e.g., nonlinear dynamics with random initial conditions.

Corbetta, Matteo↗
NASA NTRS2017

Global Energetics of Solar Flares. V. Energy Closure in Flares and Coronal Mass Ejections

In this study we synthesize the results of four previous studies on the global energetics of solar flares and associated coronal mass ejections (CMEs), which include magnetic, thermal, nonthermal, and CME energies in 399 solar M and X-class flare events observed during the first 3.5 years of the Solar Dynamics Observatory (SDO) mission. Our findings are: (1) The sum of the mean nonthermal energy of flare-accelerated particles (E(sub nt)), the energy of direct heating (E(sub dir)), and the energy in coronal mass ejections (E(sub CME)), which are the primary energy dissipation processes in a flare, is found to have a ratio of (E(sub nt)+E(sub dir)+E(sub CME))/E(sub mag) = 0.87±0.18, compared with the dissipated magnetic free energy E(sub mag), which confirms energy closure within the measurement uncertainties and corroborates the magnetic origin of flares and CMEs; (2) The energy partition of the dissipated magnetic free energy is: 0.51±0.17 in nonthermal energy of ≥ 6 keV electrons, 0.17± 0.17 in nonthermal ≥ 1 MeV ions, 0.07 ± 0.14 in CMEs, and 0.07 ± 0.17 in direct heating; (3) The thermal energy is almost always less than the nonthermal energy, which is consistent with the thick-target model; (4) The bolometric luminosity in white-light flares is comparable with the thermal energy in soft X-rays (SXR); (5) Solar Energetic Particle (SEP) events carry a fraction ≈ 0.03 of the CME energy, which is consistent with CME-driven shock acceleration; and (6) The warm-target model predicts a lower limit of the low-energy cutoff at ec ≈ 6 keV, based on the mean differential emission measure (DEM) peak temperature of T(sub e) = 8.6 MK during flares. This work represents the first statistical study that establishes energy closure in solar flare/CME events.

Solar activity↗
DOE OSTI2021

Event-Based Analysis of Solar Power Distribution Feeder Using Micro-PMU Measurements

Solar distribution feeders are commonly used in solar farms that are integrated into distribution substations. In this paper, we focus on a real-world solar distribution feeder and conduct an event-based analysis by using micro-PMU measurements. The solar distribution feeder of interest is a behind-the-meter solar farm with a generation capacity of over 4 MW that has about 200 low-voltage distributed photovoltaic (PV) inverters. The event-based analysis in this study seeks to address the following practical matters. First, we conduct event detection by using an unsupervised machine learning approach. For each event, we determine the event’s source region by an impedancebased analysis, coupled with a descriptive analytic method. We segregate the events that are caused by the solar farm, i.e., locallyinduced events, versus the events that are initiated in the grid, i.e., grid-induced events, which caused a response by the solar farm. Second, for the locally-induced events, we examine the impact of solar production level and other significant parameters to make statistical conclusions. Third, for the grid-induced events, we characterize the response of the solar farm; and make comparisons with the response of an auxiliary neighboring feeder to the same events. Fourth, we scrutinize multiple specific events; such as by revealing the dynamics to the control system of the solar distribution feeder. The results and discoveries in this study are informative to utilities and solar power industry.

14 SOLAR ENERGY↗
NASA NTRS2017

Global Energetics of Solar Flares. V. Energy Closure in Flares and Coronal Mass Ejections

In this study we synthesize the results of four previous studies on the global energetics of solar flares and associated coronal mass ejections (CMEs), which include magnetic, thermal, nonthermal, and CME energies in 399 solar M and X-class flare events observed during the first 3.5 years of the Solar Dynamics Observatory (SDO) mission. Our findings are: (1) The sum of the mean nonthermal energy of flare-accelerated particles (E(sub nt)), the energy of direct heating (E(sub dir)), and the energy in coronal mass ejections (E(sub CME)), which are the primary energy dissipation processes in a flare, is found to have a ratio of (E(sub nt) + E(sub dir) + E(sub CME))/E(sub mag) = 0.87±0.18, compared with the dissipated magnetic free energy E(sub mag), which confirms energy closure within the measurement uncertainties and corroborates the magnetic origin of flares and CMEs; (2) The energy partition of the dissipated magnetic free energy is: 0.51±0.17 in nonthermal energy of ≥ 6 keV electrons, 0.17± 0.17 in nonthermal ≥ 1 MeV ions, 0.07 ± 0.14 in CMEs, and 0.07 ± 0.17 in direct heating; (3) The thermal energy is almost always less than the nonthermal energy, which is consistent with the thick-target model; (4) The bolometric luminosity in white-light flares is comparable with the thermal energy in soft X-rays (SXR); (5) Solar Energetic Particle (SEP) events carry a fraction ≈ 0.03 of the CME energy, which is consistent with CME-driven shock acceleration; and (6) The warm-target model predicts a lower limit of the low-energy cutoff at e(sub c) ≈ 6 keV, based on the mean differential emission measure (DEM) peak temperature of T(sub e) = 8.6 MK during flares. This work represents the first statistical study that establishes energy closure in solar flare/CME events.

Solar activity↗
NASA NTRS2017

Global Energetics of Solar Flares and CMEs: V. Energy Closure

In this study we synthesize the results of four previous studies on the global energetics of solar flares and associated coronal mass ejections (CMEs), which include magnetic, thermal, nonthermal, and CME energies in 399 solar M and X-class flare events observed during the first 3.5 years of the Solar Dynamics Observatory (SDO) mission. Our findings are: (1) The sum of the mean nonthermal energy of flare-accelerated particles (E(sub nt)), the energy of direct heating (E(sub dir)), and the energy in coronal mass ejections (E(sub CME)), which are the primary energy dissipation processes in a flare, is found to have a ratio of (E(sub nt)+E(sub dir)+E(sub CME))/E(sub mag) = 0.87±0.18, compared with the dissipated magnetic free energy E(sub mag), which confirms energy closure within the measurement uncertainties and corroborates the magnetic origin of flares and CMEs; (2) The energy partition of the dissipated magnetic free energy is: 0.51±0.17 in nonthermal energy of ≥ 6 keV electrons, 0.17± 0.17 in nonthermal ≥ 1 MeV ions, 0.07 ± 0.14 in CMEs, and 0.07 ± 0.17 in direct heating; (3) The thermal energy is almost always less than the nonthermal energy, which is consistent with the thick-target model; (4) The bolometric luminosity in white-light flares is comparable with the thermal energy in soft X-rays (SXR); (5) Solar Energetic Particle (SEP) events carry a fraction ≈ 0.03 of the CME energy, which is consistent with CME-driven shock acceleration; and (6) The warm-target model predicts a lower limit of the low-energy cutoff at e(sub c) ≈ 6 keV, based on the mean differential emission measure (DEM) peak temperature of T(sub e) = 8.6 MK during flares. This work represents the first statistical study that establishes energy closure in solar flare/CME events.

Solar activity↗
DOE OSTI2023

Understanding the Shift of Drivers of Soil Erosion and Sedimentation Based on Regional Process-Based Modeling in the Mississippi River Basin During the Past Century

Soil erosion and sedimentation problems remain a major water quality concern for making watershed management policies in the Mississippi River Basin (MRB). It is unclear whether the observed decreasing trend of stream suspended sediment loading to the mouth of the MRB over the last eight decades truly reflects a decline in upland soil erosion in this large basin. Here, for this work, we improved a distributed regional land surface model, the Dynamic Land Ecosystem Model, to evaluate how climate and land use changes have impacted soil erosion and sediment yield over the entire MRB during the past century. Model results indicate that total sediment yield significantly increased during 1980–2018, despite no significant increase in annual precipitation and runoff. The increased soil erosion and sediment yield are mainly driven by intensified extreme precipitation (EP). Spatially, we found notable intensified EP events in the cropland-dominated Midwest region, resulting in a substantial increase in soil erosion and sediment yield. Land use change played a critical role in determining sediment yield from the 1910s to the 1930s, thereafter, climate variability increasingly became the dominant driver of soil erosion, which peaked in the 2010s. This study highlights the increasing influences of extreme climate in affecting soil erosion and sedimentation, thus, water quality. Therefore, existing forest and cropland Best Management Practices should be revisited to confront the impacts of climate change on water quality in the MRB.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Microbial growth under drought is confined to distinct taxa and modified by potential future climate conditions

Climate change increases the frequency and intensity of drought events, affecting soil functions including carbon sequestration and nutrient cycling, which are driven by growing microorganisms. Yet we know little about microbial responses to drought due to methodological limitations. Here, we estimate microbial growth rates in montane grassland soils exposed to ambient conditions, drought, and potential future climate conditions (i.e., soils exposed to 6 years of elevated temperatures and elevated CO 2 levels). For this purpose, we combined 18 O-water vapor equilibration with quantitative stable isotope probing (termed ‘vapor-qSIP’) to measure taxon-specific microbial growth in dry soils. In our experiments, drought caused >90% of bacterial and archaeal taxa to stop dividing and reduced the growth rates of persisting ones. Under drought, growing taxa accounted for only 4% of the total community as compared to 35% in the controls. Drought-tolerant communities were dominated by specialized members of the Actinobacteriota, particularly the genus Streptomyces. Six years of pre-exposure to future climate conditions (3 °C warming and + 300 ppm atmospheric CO 2 ) alleviated drought effects on microbial growth, through more drought-tolerant taxa across major phyla, accounting for 9% of the total community. Our results provide insights into the response of active microbes to drought today and in a future climate, and highlight the importance of studying drought in combination with future climate conditions to capture interactive effects and improve predictions of future soil-climate feedbacks.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Computational Analysis and Optimized Modeling of Geomagnetically Induced Currents in Power Transformers

In this project we aim to better understand the effect of geomagnetically induced currents (GIC) on power transformers. Expanding upon our previous work focused on producing a methodology for accuracy-enhanced computation of GIC signatures (i.e., time-domain current magnitude variation for the event duration) from a combination of physics-based and data-driven computational tools, we propose the use of these GIC signatures as inputs for a physically-detailed and optimized model of the power transformer to investigate how GIC determination and transformer modeling influence the evaluation of GIC effects on the transformer operation, as well as in its interaction with the power grid.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Methane Removal from Air: Challenges and Opportunities

Driven by increasing greenhouse gas (GHG) concentrations in the atmosphere, extreme weather events have become more frequent and their impacts on human lives have become more severe. Therefore, the need for short-term GHG mitigations is urgent. Recently, methane has been recognized as an important mitigation target due to its high global warming potential (GWP). However, methane’s low concentration in the atmosphere and stable molecular structure make its removal from the air highly challenging. This review first discusses the fundamental aspects of the challenges in atmospheric methane removal and then briefly reviews the existing research strategies following the mechanisms of natural methane sinks. Although still in its infancy, recent research on methane removal from the air holds great potential for slowing down global warming. At the same time, it is important to carefully examine the energy consumption of these methane removal strategies and whether they will be able to achieve net GHG reduction. In addition, due to the scale of methane removal from the air, any potential solution’s environmental impacts must be carefully evaluated before it can be implemented in practice.

54 ENVIRONMENTAL SCIENCES↗