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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 1,225 records · Page 68
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

The impact of collisionality on the runaway electron avalanche during a tokamak disruption

The exponential growth (avalanching) of runaway electrons (REs) during a tokamak disruption continues to be a large uncertainty in RE modeling. The present work investigates the impact of tokamak geometry on the efficiency of the avalanche mechanism across a broad range of disruption scenarios. It is found that the parameter ν *,crit ⁠, describing the collisionality at the critical energy to run away, delineates how toroidal geometry impacts RE formation. In particular, utilizing a reduced but self-consistent description of plasma power balance, it is shown that for a high-density deuterium-dominated plasma, ν *,crit is robustly less than one, resulting in a substantial decrease in the efficiency of the RE avalanche compared to predictions from slab geometry. In contrast, for plasmas containing a substantial quantity of neon or argon, ν *,crit ≳1, no reduction of the avalanche is observed due to toroidal geometry. This sharp contrast in the impact of low- vs high-Z material results primarily from the relatively strong radiative cooling from high-Z impurities, enabling the plasma to be radiatively pinned at low temperatures and thus large electric fields, even for modest quantities of high-Z material.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Autonomous x-ray scattering

Autonomous experimentation (AE) is an emerging paradigm that seeks to automate the entire workflow of an experiment, including—crucially—the decision-making step. Beyond mere automation and efficiency, AE aims to liberate scientists to tackle more challenging and complex problems. We describe our recent progress in the application of this concept at synchrotron x-ray scattering beamlines. We automate the measurement instrument, data analysis, and decision-making, and couple them into an autonomous loop. We exploit Gaussian process modeling to compute a surrogate model and associated uncertainty for the experimental problem, and define an objective function exploiting these. We provide example applications of AE to x-ray scattering, including imaging of samples, exploration of physical spaces through combinatorial methods, and coupling to in situ processing platforms These uses demonstrate how autonomous x-ray scattering can enhance efficiency, and discover new materials.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2025

Backlighting extended gas halos around luminous red galaxies: Kinematic Sunyaev-Zel’dovich effect from DESI Y1 and ACT data

The gas density profile around galaxies, shaped by feedback and affecting the galaxy lensing signal, is imprinted on the cosmic microwave background (CMB) by the kinematic Sunyaev-Zel’dovich effect (kSZ). We precisely measure this effect (𝑆/𝑁 ≈ 10) via velocity stacking with 825,283 spectroscopically confirmed luminous red galaxies (LRG) from the Dark Energy Spectroscopic Instrument Year 1 (DESI Y1) survey, which overlap with the Atacama Cosmology Telescope (ACT) Data Release 6 temperature maps over ≥ 4,000 deg 2 . We explore the kSZ dependence with various galaxy parameters and find no significant trend with redshift but clear trends with stellar mass and absolute magnitude in 𝑔, 𝑟, and 𝑧 bands. Our analysis suggests that the gas extends beyond the dark matter halo (99.5% confidence level, i.e., probability to exceed (PTE)⁢ = 0.005). We find a tentative preference for hydrodynamical simulation models with stronger feedback that drives gas further out (Illustris 𝑧 = 0.5, PTE⁢ = 0.37) over weaker-feedback cases (IllustrisTNG 𝑧 = 0.8, PTE⁢ = 0.045), though with limited statistical significance. In all cases, a free multiplicative amplitude was fit to the simulated profiles, and further modeling work is required to firm up these conclusions. We find consistency between kSZ profiles around spectroscopic and photometric LRG, with comparable statistical power, thus increasing our confidence in the photometric analysis. Additionally, we present the first kSZ measurement around the DESI Y1 bright galaxy sample (BGS) and the emission-line galaxies (ELG) whose features match qualitative expectations. Finally, we forecast 𝑆/𝑁 ∼ 50 for future stacked kSZ measurements using data from the ACT, the DESI Y3, and the Rubin Observatory. Furthermore, these measurements will serve as an input for galaxy formation models and baryonic uncertainties in galaxy lensing.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

New constraints on the Al 25 ( p , γ ) reaction and its influence on the flux of cosmic γ rays from classical nova explosions

The astrophysical 25 Al(p,γ) 26 Si reaction represents one of the key remaining uncertainties in accurately modeling the abundance of radiogenic 26 Al ejected from classical novae. Specifically, the strengths of key proton-unbound resonances in 26 Si, that govern the rate of the 25 Al(p,γ) reaction under explosive astrophysical conditions, remain unsettled. Here, we present a detailed spectroscopy study of the 26 Si mirror nucleus 26 Mg. We have measured the lifetime of the 3 + , 6.125-MeV state in 26 Mg to be 19(3) fs and provide compelling evidence for the existence of a 1 – state in the T = 1, A = 26 system, indicating a previously unaccounted for ℓ = 1 resonance in the 25 Al(p,γ) reaction. Using the presently measured lifetime, together with the assumption that the likely 1 – state corresponds to a resonance in the 25 Al + p system at 435.7(53) keV, we find considerable differences in the 25 Al(p,γ) reaction rate compared to previous works. Furthermore, based on current nova models, we estimate that classical novae may be responsible for up to ≈ 15% of the observed galactic abundance of 26 Al.

20 ≤ A ≤ 38↗
DOE OSTI2025

Proton emission in ultraperipheral Pb-Pb collisions at $\sqrt{𝑠_{𝑁⁢𝑁}}$ = 5.02 TeV

The first measurements of proton emission accompanied by neutron emission in the electromagnetic dissociation (EMD) of 208 Pb nuclei in the ALICE experiment at the Large Hadron Collider are presented. The EMD protons and neutrons emitted at very forward rapidities are detected by the proton and neutron zero degree calorimeters of the ALICE experiment. The emission cross sections of zero, one, two, and three protons accompanied by at least one neutron were measured in ultraperipheral 208 Pb − 208 Pb collisions at a center-of-mass energy per nucleon pair $\sqrt{𝑠_{𝑁⁢𝑁}}$ = 5.02TeV. The 0p and 3p cross sections are described by the RELDIS model within their measurement uncertainties, while the 1p and 2p cross sections are underestimated by the model by 17–25%. According to this model, these 0p, 1p, 2p, and 3p cross sections are associated, respectively, with the production of various isotopes of Pb, Tl, Hg, and Au in the EMD of 208 Pb . The cross sections of the emission of a single proton accompanied by the emission of one, two, or three neutrons in EMD were also measured. The data are significantly overestimated by the RELDIS model, which predicts that the (1p,1n), (1p,2n), and (1p,3n) cross sections are very similar to the cross sections for the production of the thallium isotopes 206,205,204 Tl.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Neutrino-nucleus CC 0 π cross-section tuning in GENIE v3

This article summarizes the state of the art of v μ and $\bar{v}_μ$ CC0π cross-section measurements on carbon and argon and discusses the relevant nuclear models, parametrizations and uncertainties in GENIE v3. The CC0π event topology is common in experiments at a few-GeV energy range. Although its main contribution comes from quasi-elastic interactions, this topology is still not well understood. The GENIE global analysis framework is exploited to analyze CC0π datasets from MiniBooNE, T2K and MINERvA. A partial tune for each experiment is performed, providing a common base for the discussion of tensions between datasets. The results offer an improved description of nuclear CC0π datasets as well as data-driven uncertainties for each experiment. This work is a step towards a GENIE global tune that improves our understanding of neutrino interactions on nuclei. It follows from earlier GENIE work on the analysis of neutrino scattering datasets on hydrogen and deuterium.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2026

Measurement of the Higgs boson total decay width using the 𝐻 → 𝑊⁢𝑊 → 𝑒⁢𝜈⁢𝜇⁢𝜈 decay channel in proton-proton collisions at $\sqrt{s} =13$ TeV

The Higgs boson (H) decay width is determined from the ratio of off- and on-shell production of 𝐻 → 𝑊⁢𝑊 → 𝑒⁢𝜈⁢𝜇⁢𝜈 using proton–proton collision data corresponding to an integrated luminosity of 138 fb −1 collected at $\sqrt{s} =13$ TeV by the CMS experiment at the Large Hadron Collider. The off-shell signal strength is measured as 𝜇 off−shell = $1.2^{+0.8}_{−0.7}$. The Higgs boson total decay width is Γ 𝐻 = $3.9^{+2.7}_{−2.2}$ MeV, in agreement with the standard model prediction. The uncertainty in this result represents a factor of 3 improvement over the previous CMS result in this decay channel.

Hayrapetyan, A. [Yerevan Physics Institute]↗
DOE OSTI2022

MatPhase: Material phase prediction for Li-ion Battery Reconstruction using Hierarchical Curriculum Learning

Li-ion Batteries (LIB), one of the most efficient energy storage devices, are used extensively in many industrial applications. These batteries consist of electrodes that are put together with heterogeneous material compositions. Imaging data of these battery electrodes obtained from X-ray tomography can explain the distribution of material constituents and allow reconstructions to study electron transport pathways. Such reconstructions of material constituents help quantify various associated properties of electrodes (e.g., volume-specific surface area, porosity) which determine the performance of batteries. These images often suffer from low image contrast between multiple material constituents, hence making it difficult for humans to distinguish and characterize these constituents through visual inspection. A minor error in detecting distributions of the material constituents can lead to magnified errors in the calculated parameters of material properties (e.g., porosity). We present MatPhase, a novel hierarchical curriculum learning technique to address the complex task of estimating material constituent distribution in battery electrodes. MatPhase comprises three modules: (i) an uncertainty-aware global model trained to yield inferences conditioned upon global knowledge of material distribution, (ii) a local model to capture relatively more fine-grained (local) distributional signals, (iii) an aggregator model to appropriately fuse the local and global effects towards obtaining the final distribution. On average, MatPhase improves prediction up to 8.5% relative to other sophisticated modeling pipelines and state-of-the-arts (SOTA) object detection models employed in the performance comparison.

Tabassum, Anika↗
DOE OSTI2020

Reserve Model of Energy Storage in Day-ahead Joint Energy and Reserve Markets: A Stochastic UC Solution

With many favorable advantages including fast response ability in particular, utility-level energy storage systems (ESS) are being integrated into energy and reserve markets to help mitigate uncertain renewable resources and fluctuant demands. This paper discusses a stochastic unit commitment (UC) model to explore capabilities of ESSs in providing valuable grid services by simultaneously joining energy and reserve markets. The proposed reserve model of ESSs presents the following features: (i) two constraints are proposed to formulate ESS’s reserve provision ability in each hour via six operation modes, namely increasing/reducing the level of charge, switching to discharge, increasing/reducing the level of discharge, switching to charge; (ii) as an energy-limited asset, constraints on ESS’s reserve deliverability across multiple hours is introduced to hold enough state of charge (SOC) headroom and floor room, guaranteeing that reserves cleared in individual hours are continuously deliverable over multiple successive hours without violating operation limits. Furthermore, a scenario-based UC model, which addresses uncertainties of renewables and demands, is adopted to evaluate reserves provided by ESSs and generators. To effectively solve the stochastic UC problem, the progressive hedging algorithm with heuristic approaches is discussed. A 6-bus system and a modified IEEE 118-bus system are used to illustrate effectiveness of the proposed approaches.

25 ENERGY STORAGE↗
DOE OSTI2023

Desorption and Co–Dissolution of Uranium–Bearing Solids During Alkalinity–Enhanced Flushing of Contaminated Sediments

Elevated uranium concentrations in groundwater remain a persistent challenge at contaminated sites. Several sites rely on natural flushing of uranium as a remediation strategy. Uncertainties in conceptual models can cause remediation strategies to underestimate timeframes required to reach remediation goals. In this study, laboratory experiments were conducted to investigate uranium flushing of sediments from a site with persistent groundwater contamination. Six columns were used to simulate alkalinity-enhanced flushing of uranium from sediments, by switching influent alkalinity after ~12 pore volumes. About 20% to 31% of sediment uranium was consistently flushed from the sediments. K d values varied greatly (5.3 to 117 L/kg) but were consistently lower (20% to 50%) during influents with elevated alkalinity. The mass of uranium recovered from the columns also was consistently higher (5% to 80%) during alkalinity-enhanced flushing periods. However, column experiments with sequentially increasing alkalinity showed diminishing returns in uranium elution at higher carbonate concentrations. The loss of flushing efficiency is attributed to significant calcite precipitation at higher alkalinities. Furthermore, the results show that alkalinity-enhanced flushing of uranium could be employed as a viable remediation scheme if calcite precipitation could be minimized in a field application.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2022

Implementation of a Model Predictive Control Strategy to Regulate Temperature Inside Plug-Flow Solar Reactor With Countercurrent Flow

Abstract Solar-driven thermochemical energy storage systems are proven to be promising energy carriers (solar fuels) to utilize solar energy by using reactive solid-state pellets. However, the production of solar fuel requires a quasi-steady-state process temperature, which represents the main challenge due to the transient nature of solar power. In this work, an adaptive model predictive controller (MPC) is presented to regulate the temperature inside a tubular solar reactor to produce solid-state solar fuel for long-term thermal storage systems. The solar reactor system consists of a vertical tube heated circumferentially over a segment of its length by concentrated solar power, and the reactive pellets (MgMn2O4) are fed from the top end and flow downwards through the heated tube. A countercurrent flowing gas supplied from the lower end interacts with flowing pellets to reduce it thermochemically at a temperature range of 1000—1500 °C. A low-order physical model was developed to simulate the dynamics of the solar reactor including the reaction kinetics, and the proposed model was validated numerically by using a 7-kW electric furnace. The numerical model then was utilized to design the MPC controller, where the control system consists of an MPC code linked to an adaptive system identification code that updates system parameters online to ensure system robustness against external disturbances (sudden change in the flow inside the reactor), model mismatches, and uncertainty. The MPC controller parameters are tuned to enhance the system performance with minimum steady-state error and overshoot. The controller is tested to track different temperature ranges between 500 °C and 1400 °C with different particles/gas mass flowrates and ramping temperature profiles. Results show that the MPC controller successfully regulated the reactor temperature within ± 1 °C of its setpoint and maintained robust performance with minimum input effort when subjected to sudden changes in the amount of flowing media and the presence of chemical reaction.

Engineering↗
DOE OSTI2022

Neutrino emission from binary neutron star mergers: characterising light curves and mean energies

Abstract Neutrinos are copiously emitted by neutron star mergers, due to the high temperatures reached by dense matter during the merger and its aftermath. Neutrinos influence the merger dynamics and shape the properties of the ejecta, including the resulting r -process nucleosynthesis and kilonova emission. In this work, we analyse neutrino emission from a large sample of binary neutron star merger simulations in Numerical Relativity, covering a broad range of initial masses, nuclear equation of state and viscosity treatments. We extract neutrino luminosities and mean energies, and compute quantities of interest such as the peak values, peak broadnesses, time averages and decrease time scales. We provide a systematic description of such quantities, including their dependence on the initial parameters of the system. We find that for equal-mass systems the total neutrino luminosity (several $$10^{53}{\hbox {erg}~{\hbox {s}}^{-1}}$$ 10 53 erg s - 1 ) decreases as the reduced tidal deformability increases, as a consequence of the less violent merger dynamics. Similarly, tidal disruption in asymmetric mergers leads to systematically smaller luminosities. Peak luminosities can be twice as large as the average ones. Electron antineutrino luminosities dominate (initially by a factor of 2-3) over electron neutrino ones, while electron neutrinos and heavy flavour neutrinos have similar luminosities. Mean energies are nearly constant in time and independent on the binary parameters. Their values reflect the different decoupling temperature inside the merger remnant. Despite present uncertainties in neutrino modelling, our results provide a broad and physically grounded characterisation of neutrino emission, and they can serve as a reference point to develop more sophisticated neutrino transport schemes.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Measurement of the differential $\hbox {t}\overline{\hbox {t}}$ production cross section as a function of the jet mass and extraction of the top quark mass in hadronic decays of boosted top quarks

A measurement of the jet mass distribution in hadronic decays of Lorentz-boosted top quarks is presented. The measurement is performed in the lepton + jets channel of top quark pair production ($\hbox {t}\overline{\hbox {t}}$) events, where the lepton is an electron or muon. The products of the hadronic top quark decay are reconstructed using a single large-radius jet with transverse momentum greater than 400 GeV. The data were collected with the CMS detector at the LHC in proton-proton collisions and correspond to an integrated luminosity of 138 fb -1 . The differential $\hbox {t}\overline{\hbox {t}}$ production cross section as a function of the jet mass is unfolded to the particle level and is used to extract the top quark mass. The jet mass scale is calibrated using the hadronic W boson decay within the large-radius jet. The uncertainties in the modelling of the final state radiation are reduced by studying angular correlations in the jet substructure. These developments lead to a significant increase in precision, and a top quark mass of 173.06 ± 0.84 GeV.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Measurements of the Higgs boson production cross section and couplings in the W boson pair decay channel in proton-proton collisions at $\sqrt{s}=13\,\text {Te\hspace{-.08em}V} $

Production cross sections of the standard model Higgs boson decaying to a pair of W bosons are measured in proton-proton collisions at a center-of-mass energy of 13$\,\text {Te\hspace{-.08em}V}$. The analysis targets Higgs bosons produced via gluon fusion, vector boson fusion, and in association with a W or Z boson. Candidate events are required to have at least two charged leptons and moderate missing transverse momentum, targeting events with at least one leptonically decaying W boson originating from the Higgs boson. Results are presented in the form of inclusive and differential cross sections in the simplified template cross section framework, as well as couplings of the Higgs boson to vector bosons and fermions. The data set collected by the CMS detector during 2016–2018 is used, corresponding to an integrated luminosity of 138$\,\text {fb}^{-1}$. The signal strength modifier $\mu $, defined as the ratio of the observed production rate in a given decay channel to the standard model expectation, is measured to be $\mu = 0.95^{+0.10}_{-0.09}$. All results are found to be compatible with the standard model within the uncertainties.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

LTAU-FF: Loss Trajectory Analysis for Uncertainty in atomistic Force Fields

LTAU (Loss Trajectory Analysis for Uncertainty) is a technique for estimating the uncertainty in a model's predictions for any regression task by approximating the cumulative distribution function (CDF) of the model's errors over the course of training. The approximated CDF, combined with a similarity search algorithm in the model's descriptor space, can then be used to estimate the likelihood that the model's predictions on any given test point will fall below a chosen threshold. LTAU-FF (LTAU in atomistic Force Fields) is the application of LTAU specifically for use with atomistic force fields.

Vita, JoshuaA↗
DOE OSTI2024

SOURCES4D

SOURCES is a code for computing neutron source rates and spectra from spontaneous fission (including delayed neutrons) and (alpha,n) reactions in homogeneous materials and (alpha,n) reactions in single-interface and two-interface geometries. SOURCES is a Los Alamos National Laboratory (LANL) code that is written in FORTRAN and distributed through the Radiation Safety Information Computation Center (RSICC). LANL’s last release of SOURCES to RSICC was SOURCES4C in 2002. This disclosure covers the latest version of SOURCES, SOURCES4D. This version adds sensitivity capabilities for (alpha,n) sources in homogeneous materials. Specifically, SOURCES4D writes new output that can be used to calculate, in post-processing, first and second derivatives of the (alpha,n) source rate density and spectrum with respect to nuclide densities in a homogeneous material and first derivatives of the (alpha,n) source rate density and spectrum with respect to nuclide stopping powers and (alpha,n) cross sections (nuclear data). These derivatives are useful for uncertainty quantification, predictive modeling, and other applications in neutron transport problems.

Favorite, Jeffrey A.↗
DOE OSTI2025

Adaptive Computing (AC) [SWR-24-106]

The Adaptive Computing (AC) software stack supports goal-based computing, for which a simulation workload is created on the fly adapting to the results of calculations. Application-specific code defines an objective, which may be to solve an optimization problem or to train a surrogate model with minimal uncertainty. Then, the AC driver decides where in the design parameter space to run simulations to best achieve that objective. This process is iterative and online; as new data is returned from simulations, the AC driver chooses new simulations to run. The AC driver can strategically run simulations on distributed hardware resources (including high performance computing machines, cloud resources, and edge devices) to maximize throughput and obey resource constraints.

Griffin, Kevin [National Renewable Energy Laborato↗
DOE OSTI2026

Adaptive Computing (AC) (Open Source) [SWR-24-106]

The Adaptive Computing (AC) software stack supports goal-based computing, for which a simulation workload is created on the fly, adapting to the results of calculations. Application-specific code defines an objective, which may be to solve an optimization problem or to train a surrogate model with minimal uncertainty. Then, the AC driver decides where in the design parameter space to run simulations to best achieve that objective. This process is iterative and online; as new data is returned from simulations, the AC driver chooses new simulations to run. The AC driver can strategically run simulations on distributed hardware resources (including high performance computing machines, cloud resources, and edge devices) to maximize throughput and obey resource constraints.

Griffin, Kevin [National Laboratory of the Rockies↗