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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 685 records · Page 38
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Search for Supersymmetry with a Compressed Mass Spectrum in Events with a Soft $\tau$ Lepton, a Highly Energetic Jet, and Large Missing Transverse Momentum in Proton-Proton Collisions at $\sqrt{s}=$ TeV

The first search for supersymmetry in events with an experimental signature of one soft, hadronically decaying τ lepton, one energetic jet from initial-state radiation, and large transverse momentum imbalance is presented. These event signatures are consistent with direct or indirect production of scalar τ leptons (τ˜) in supersymmetric models that exhibit coannihilation between the τ˜ and the lightest neutralino (χ˜10), and that could generate the observed relic density of dark matter. The data correspond to an integrated luminosity of 77.2 fb-1 of proton-proton collisions at s=13 TeV collected with the CMS detector at the LHC in 2016 and 2017. The results are interpreted in a supersymmetric scenario with a small mass difference (Δm) between the chargino (χ˜1±) or next-to-lightest neutralino (χ˜20), and the χ˜10. The mass of the τ˜ is assumed to be the average of the χ˜1± and χ˜10 masses. The data are consistent with standard model background predictions. Upper limits at 95% confidence level are set on the sum of the χ˜1±, χ˜20, and τ˜ production cross sections for Δm(χ˜1±,χ˜10)=50 GeV, resulting in a lower limit of 290 GeV on the mass of the χ˜1±, which is the most stringent to date and surpasses the bounds from the LEP experiments.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Measurement of the J / ψ Polarization with Respect to the Event Plane in Pb-Pb Collisions at the LHC

We study the polarization of inclusive J/ψ produced in Pb-Pb collisions at $\sqrt{^sNN}$ = 5.02 TeV at the LHC in the dimuon channel, via the measurement of the angular distribution of its decay products. We perform the study in the rapidity region 2.5 < y < 4, for three transverse momentum intervals (2 < p T < 4, 4 < p T < 6, 6 < p T < 10 GeV/c) and as a function of the centrality of the collision for 2 < p T < 6 GeV/c. For the first time, the polarization is measured with respect to the event plane of the collision, by considering the angle between the positive-charge decay muon in the J/ψ rest frame and the axis perpendicular to the event-plane vector in the laboratory system. A small transverse polarization is measured, with a significance reaching 3.9σ at low p T and for intermediate centrality values. The polarization could be connected with the behavior of the quark-gluon plasma, formed in Pb-Pb collisions, as a rotating fluid with large vorticity, as well as with the existence of a strong magnetic field in the early stage of its formation.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2026

Charge-trap analysis in a SENSEI skipper-CCD: Understanding low-energy backgrounds in rare-event searches

Skipper charge-coupled devices (CCDs) are ultralow-threshold detectors capable of detecting energy deposits in silicon at the electronvolt scale. Skipper CCDs are increasingly used in rare-event searches, including experiments such as SENSEI, DAMIC-M, Oscura, and CONNIE, where one of the major challenges is mitigating low-energy backgrounds. In this work, we present results on trap characterization in a silicon skipper-CCD produced in the same fabrication run as the SENSEI experiment at SNOLAB. Lattice defects contribute to backgrounds in rare-event searches through single-electron charge trapping. To investigate this, we use the charge-pumping technique at different temperatures to identify dipoles produced by traps in the CCD channel. We fully characterize a fraction of these traps and use this information to extrapolate their contribution to the single-electron background in SENSEI. We find that this subpopulation of traps does not contribute significantly, but more work is needed to assess the impact of the traps that cannot be characterized.

Brusco, Agustin↗
DOE OSTI2026

Improving neutrino oscillation measurements through event classification

Precise neutrino energy reconstruction is essential for next-generation long-baseline oscillation experiments, yet current methods remain limited by large uncertainties in neutrino-nucleus interaction modeling. Even so, it is well established that different interaction channels produce systematically varying amounts of missing energy and therefore yield different reconstruction performance–information that standard calorimetric approaches do not exploit. We introduce a strategy that incorporates this structure by classifying events according to their underlying interaction type prior to energy reconstruction. Using supervised machine-learning techniques trained on labeled generator events, we leverage intrinsic kinematic differences among quasielastic scattering, meson-exchange current, resonance production, and deep-inelastic scattering processes. A cross-generator testing framework demonstrates that this classification approach is robust to microphysics mismodeling and, when applied to a simulated DUNE 𝜈 𝜇 disappearance analysis, yields improved accuracy and sensitivity at the 10%–20% level. These results highlight a practical path toward reducing reconstruction-driven systematics in future oscillation measurements.

Ellis, Sebastian A. R. [King's College, London (Un↗
DOE OSTI2024

Capturing Infrastructure Interdependencies for Power Outages Prediction During Extreme Events

As extreme weather events such as hurricanes, severe thunderstorms, and floods grow in frequency and intensity, the disruption of power grid systems poses significant challenges, including widespread electrical outages, economic losses, and threats to public safety. This paper presents a forward-looking approach that leverages geographical graph-based machine learning models to predict county-level maximum power outages during such events. By capturing the intricate interdependencies within power system networks, our approach aims to provide precise and actionable predictions that can optimize emergency response efforts and enhance grid resilience. Through the integration of real-world data, including hurricane advisories and power outage records, we have trained and benchmarked multiple machine learning models, demonstrating the feasibility and potential of this method. While our initial results are promising, this paper also charts a course for advancing these models, addressing the remaining challenges, and ultimately transforming how we anticipate and respond to the impacts of extreme weather on power systems.

Lee, Sangkeun (Matt) [ORNL] (ORCID:000000021317511↗
DOE OSTI2025

Rapid Event Detection via Synchro-Waveform Based Temporal Attention Network in Distributed Grid

Compared with the information collected from phasor measurement units, synchro-waveforms contain high-fidelity disturbances of the grid, which can be a granular and authentic representation of measurements in the modern power system. However, the dynamic changing morphology makes it challenging to effectively capture various disturbance information from the synchro-waveforms. To tackle this issue, this paper proposes a Synchro-waveform based Temporal Attention (STA) network to achieve rapid event detection. First, a multi-scenario distributed model with renewable integration is established to generate synchro-waveforms under various uncertainties. Then, three typical temporal features are extracted directly from the synchro-waveform measurements. Additionally, the lightweight STA network is deployed to identify the most common event types in renewable energy systems via the self-attention based vision transformer module. The results from simulated experiments demonstrate that the proposed approach can achieve rapid and real-time detection within 0.81 ms and over 96.27 % accuracy.

Dong, Yuqing [University of Tennessee (UT)]↗
DOE OSTI2025

Behavior of Multiple PV Plants in Future Power Grids During Events

As the integration of multiple photovoltaic (PV) plants into power grids grows, the dynamic response of each plant and their interactions during transient events demands a deeper understanding. In this paper, the dynamic behavior of multiple PV plants connected to future power grids is comprehensively explored using site-specific high-fidelity electromagnetic transient (EMT) PV plant models and generic high-fidelity EMT PV plant models. This research demonstrates the need to employ multiple high-fidelity EMT PV plant models to understand the intricate interactions between multiple PV plants during grid events. These models, developed in Fortran within the PSCAD environment, encompass a range of operational scenarios and plant configurations, offering invaluable insights crucial for future system planning with multiple PV plants to enhance grid stability.

Marthi, Phani Ratna Vanamali [ORNL] (ORCID:0000000↗
DOE OSTI2025

Regional Inertia Estimation Using Actual Event Measurements: Florida Case

As inverter-based resources’ integration in power grids increases, their uneven distribution across the electrical network leads to the formation of local regions that are weakly coupled to the larger interconnection. This signifies the necessity of regional frequency dynamics investigation and analyzing various inertia metrics. This paper presents a practical methodology for estimating regional rate-of-change of frequency (RoCoF) using actual event recordings, which is then used to evaluate regional inertia. Florida (FL) is selected as the region of interest due to its distinct regional frequency dynamics and the rising levels of solar generation. We identify and analyze confirmed events from 2017 to 2024 that occurred in FL. The results indicate that FL contributes about 14% to the total inertia of the US Eastern Interconnection, which approximately matches its share of generation capacity. Results also highlight seasonal fluctuations in energy generation, which play a significant role in influencing inertia and thus the RoCoF levels. This emphasizes the importance of estimating regional inertia to enhance grid operations for a future that focuses on distributed generation.

Dulal, Saurav [University of Tennessee, Knoxville ↗
DOE OSTI2025

Distribution System Resilience Assessment Considering PV Vulnerabilities for Hurricane Events

Distribution networks are increasingly vulnerable to damage and outages from extreme weather events. The integration of solar photovoltaics (PVs) further complicates resilience analysis due to its weather-dependent nature. However, limited research has examined the impacts of weather on PVs under severe events like hurricanes. This paper proposes a probabilistic framework to assess distribution system resilience considering PV vulnerabilities during hurricanes. The framework incorporates (i) a spatiotemporal fragility model to evaluate failure probabilities for distribution lines and PVs, and (ii) resilience indices at both system and component levels. The approach offers valuable insights into the resilience of modern distribution grids under extreme weather conditions. Numerical results on the unbalanced IEEE 123-bus test system validate the effectiveness of the framework.

Vahedi, Soroush [University of Connecticut, Storrs↗
DOE OSTI2022

Simulating Impacts of Extreme Events on Grids with High Penetrations of Wind Power Resources

As extreme weather events become more frequent and intense, the demand for connecting grid operation and infrastructure planning with extreme event models will increase as well. We present a methodology for creating damage contingencies and scenarios for electric transmission grids during a hurricane strike. Using WIND Toolkit meteorological data in conjunction with fragility curves for various electric grid elements, we generate stochastic damage scenarios that can be used for short- and long-term planning problems, e.g., emergency asset management. Included is an example case study: Hurricane Dolly damaging a synthetic 2000-bus test system during its landing in Southern Texas. We perform statistical analysis of damages and discuss topological effects on the example synthetic grid. Also, we include a cursory evaluation of impacts using simplified operational models. Finally, we discuss how our method can be extended to use even higher-fidelity meteorological data sets and suggest directions for future work.

contingencies↗
DOE OSTI2021

Event-Driven Predictive Approach for Real-Time Volt/VAR control with CVR in solar PV rich Active Distribution Network

The focus of this paper is on analyzing the impact of conservation voltage reduction in the presence of active devices such as solar photovoltaic (PV) and developing controls that leverage these distributed energy resources. An event-driven predictive approach for real-time volt/volt-ampere reactive (VAR) optimization, along with local two-level adaptive volt/VAR droop-based control algorithm for advanced distribution management systems, is introduced. The methodology covers aggregated and autonomous controls under different timescale operations, including the impact and effect of unpredicted events such as cloud transients on PV power production. In addition, the control schemes include the uncertainties in PV power generation and load power demand. The proposed methodology is validated in a real-time framework using the real-time digital simulator platform through co-simulation with models based on Python and OpenDSS (Open Distribution System Simulator). The developed methodology is tested on the modified IEEE 123-feeder test system. The results reveal that the proposed methodology works well in the presence of high penetrations of PV power, produces significant energy savings, and mitigates over-/undervoltage problems.

14 SOLAR ENERGY↗
DOE OSTI2020

Data-Based Resilience Enhancement Strategies for Electric-Gas Systems Against Sequential Extreme Weather Events

Some extreme weather events, such as the hurricane, pass through an area sequentially and thus are called sequential extreme weather events (SEWEs). This paper proposes a data-based robust optimization (RO) model to enhance the resilience of the integrated electricity and gas system (IEGS) against SEWEs. Specifically, the SEWE strikes the IEGS sequentially. After each attack, the system state is adjusted immediately to minimize the maximized expected system cost caused by the SEWE. The attack-defense procedures are repeated alternatively during the SEWE. Preventive measures, hardening, are made in advance to reduce the impact of sequential attacks. The entire process is formulated as a multi-period RO model. Furthermore, it is proved that the most effective resilience enhancement strategies for this model are the same as those for a two-stage RO model, which can be solved by the nested column-and-constraint generation (C&CG) algorithm. In addition, the property of SEWEs, sequentially endangering limited regions of the IEGS, is incorporated to build a data-based uncertainty set and reduce its conservativeness. Simulation results on two IEGSs validate the effectiveness of the proposed model.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Simulation of Hurricane Harvey flood event through coupled hydrologic-hydraulic models: Challenges and next steps

Using the 2017 Hurricane Harvey flood event as a test case, this study set up a series of sensitivity analyses to highlight three challenges associated with large-scale flood inundation modeling, including (a) model parameterization, (b) errors in digital elevation models, and (c) effects of reservoir retention. Driven by radar-based hourly rainfall data, a series of hydrologic-hydraulic models including the VIC hydrologic model, RAPID routing model, and Flood2D-GPU hydrodynamic model are set up over Harris County, Texas, to simulate flood inundation and hazards. The results demonstrate the importance of hydrologic parameters in improving flood modeling. For a large flood event such as Hurricane Harvey, the effect of the initial water depths is insignificant. The Manning's n values may increase the peak water depth by ~1%, the flood extents by 65km 2 , and the high danger zone by ~6%. On the contrary, the bathymetry correction factors may reduce the flood extent by ~1.4% and the high-danger zone by ~4%. Reducing the reservoir storage capacity to 1% may increase the flood extent by ~4% and the high-danger zone by ~17%. This study may provide supporting information to guide and prioritize the development of future high-performance computing hydrodynamic large-scale flood simulations.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

The role of Northeast Pacific meltwater events in deglacial climate change

Columbia River megafloods occurred repeatedly during the last deglaciation, but the impacts of this fresh water on Pacific hydrography are largely unknown. To reconstruct changes in ocean circulation during this period, we used a numerical model to simulate the flow trajectory of Columbia River megafloods and compiled records of sea surface temperature, paleo-salinity, and deep-water radiocarbon from marine sediment cores in the Northeast Pacific. The North Pacific sea surface cooled and freshened during the early deglacial (19.0-16.5 ka) and Younger Dryas (12.9-11.7 ka) intervals, coincident with the appearance of subsurface water masses depleted in radiocarbon relative to the sea surface. We infer that Pacific meltwater fluxes contributed to net Northern Hemisphere cooling prior to North Atlantic Heinrich Events, and again during the Younger Dryas stadial. Abrupt warming in the Northeast Pacific similarly contributed to hemispheric warming during the Bølling and Holocene transitions. These findings underscore the importance of changes in North Pacific freshwater fluxes and circulation in deglacial climate events.

54 ENVIRONMENTAL SCIENCES↗
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 OSTI2020

Search for physics beyond the standard model in events with jets and two same-sign or at least three charged leptons in proton-proton collisions at $\sqrt{s}=$ 13 TeV

A data sample of events from proton-proton collisions with at least two jets, and two isolated same-sign or three or more charged leptons, is studied in a search for signatures of new physics phenomena. The data correspond to an integrated luminosity of $137{\,{\text {fb}}^{-1}} $ at a center-of-mass energy of $13\,{\text {TeV}} $, collected in 2016–2018 by the CMS experiment at the LHC. The search is performed using a total of 168 signal regions defined using several kinematic variables. The properties of the events are found to be consistent with the expectations from standard model processes. Exclusion limits at 95% confidence level are set on cross sections for the pair production of gluinos or squarks for various decay scenarios in the context of supersymmetric models conserving or violating R parity. The observed lower mass limits are as large as $2.1\,{\text {TeV}} $ for gluinos and $0.9\,{\text {TeV}} $ for top and bottom squarks. To facilitate reinterpretations, model-independent limits are provided in a set of simplified signal regions.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

The cosmic muon and detector simulation framework of the extreme energy events (EEE) experiment

Abstract This paper describes the simulation framework of the extreme energy events (EEE) experiment. EEE is a network of cosmic muon trackers, each made of three multi-gap resistive plate chambers (MRPC), able to precisely measure the absolute muon crossing time and the muon integrated angular flux at the ground level. The response of a single MRPC and the combination of three chambers have been implemented in a GEANT4-based framework (GEMC) to study the telescope response. The detector geometry, as well as details about the surrounding materials and the location of the telescopes have been included in the simulations in order to realistically reproduce the experimental set-up of each telescope. A model based on the latest parametrization of the cosmic muon flux has been used to generate single muon events. After validating the framework by comparing simulations to selected EEE telescope data, it has been used to determine detector parameters not accessible by analysing experimental data only, such as detection efficiency, angular and spatial resolution.

Abbrescia, M.↗
DOE OSTI2022

Measurement of the $c$-jet mistagging efficiency in $t\bar{t}$ events using $pp$ collision data at $\sqrt{s}=13$ $\text {TeV}$ collected with the ATLAS detector

A technique is presented to measure the efficiency with which c-jets are mistagged as b-jets (mistagging efficiency) using tt¯ events, where one of the W bosons decays into an electron or muon and a neutrino and the other decays into a quark–antiquark pair. The measurement utilises the relatively large and known W → cs branching ratio, which allows a measurement to be made in an inclusive c-jet sample. The data sample used was collected by the ATLAS detector at √s = 13 TeV and corresponds to an integrated luminosity of 139 fb –1 . Events are reconstructed using a kinematic likelihood technique which selects the mapping between jets and tt¯ decay products that yields the highest likelihood value. The distribution of the b-tagging discriminant for jets from the hadronic W decays in data is compared with that in simulation to extract the mistagging efficiency as a function of jet transverse momentum. The total uncertainties are in the range 3–17%. The measurements generally agree with those in simulation but there are some differences in the region corresponding to the most stringent b-jet tagging requirement.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗