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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 1,621 records · Page 90
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Measurement of the photon identification efficiencies with the ATLAS detector using LHC Run 2 data collected in 2015 and 2016

The efficiency of the photon identification criteria in the ATLAS detector is measured using 36.1 fb 1 to 36.7 fb 1 of pp collision data at √s = 13 TeV collected in 2015 and 2016. The efficiencies are measured separately for converted and unconverted isolated photons, in four different pseudorapidity regions, for transverse momenta between 10 GeV and 1.5 TeV. The results from the combination of three data-driven techniques are compared with the predictions from simulation after correcting the variables describing the shape of electromagnetic showers in simulation for the average differences observed relative to data. Data-to-simulation efficiency ratios are determined to account for the small residual efficiency differences. These factors are measured with uncertainties between 0.5% and 5% depending on the photon transverse momentum and pseudorapidity. The impact of the isolation criteria on the photon identification efficiency, and that of additional soft pp interactions, are also discussed. The probability of reconstructing an electron as a photon candidate is measured in data, and compared with the predictions from simulation. In conclusion, the efficiency of the reconstruction of photon conversions is measured using a sample of photon candidates from Z → μμγ events, exploiting the properties of the ratio of the energies deposited in the first and second longitudinal layers of the ATLAS electromagnetic calorimeter.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

HIGH VOLTAGE DESIGN AND EVALUATION OF WIEN FILTERS FOR THE CEBAF 200 keV INJECTOR UPGRADE

High-energy nuclear physics experiments at the Jefferson Lab Continuous Electron Beam Accelerator Facility (CEBAF) require highly spin-polarization electron beams, produced from strained super-lattice GaAs photocathodes, activated to negative electron affinity in a photogun operating at 130 kV dc. A pair of Wien filter spin rotators in the injector defines the orientation of the electron beam polarization at the end station target. An upgrade of the CEBAF injector to better support the upcoming MOLLER experiment requires increasing the electron beam energy to 200 keV, to reduce unwanted helicity correlated intensity and position systematics and provide precise control of the polarization orientation. Our contribution describes design, fabrication and testing of the high voltage system to upgrade the Wien spin rotator to be compatible with the 200 keV beam. This required Solidworks modeling, CST and Opera electro- and magnetostatic simulations, upgrading HV vacuum feedthroughs, and assembly techniques for improving electrode alignment. The electric and magnetic fields required by the Wien condition and the successful HV characterization under vacuum conditions are also presented.

Palacios-Serrano, G.↗
DOE OSTI2015

Damping Ring R&D at CESR-TA

Accelerators that collide high energy beams of matter and anti-matter are essential tools for the investigation of the fundamental constituents of matter, and the search for new forms of matter and energy. A “Linear Collider” is a machine that would bring high energy and very compact bunches of electrons and positrons (anti-electrons) into head-on collision. Such a machine would produce (among many other things) the newly discovered Higgs particle, enabling a detailed study of its properties. Among the most critical and challenging components of a linear collider are the damping rings that produce the very compact and intense beams of electrons and positrons that are to be accelerated into collision. Hot dilute particle beams are injected into the damping rings, where they are compressed and cooled. The size of the positron beam must be reduced more than a thousand fold in the damping ring, and this compression must be accomplished in a fraction of a second. The cold compact beams are then extracted from the damping ring and accelerated into collision at high energy. The proposed International Linear Collider (ILC), would require damping rings that routinely produce such cold, compact and intense beams. The goal of the Cornell study was a credible design for the damping rings for the ILC. Among the technical challenges of the damping rings; the development of instrumentation that can measure the properties of the very small beams in a very narrow window of time, and mitigation of the forces that can destabilize the beams and prevent adequate cooling, or worse lead to beam loss. One of the most pernicious destabilizing forces is due to the formation of clouds of electrons in the beam pipe. The electron cloud effect is a phenomenon in particle accelerators in which a high density of low energy electrons, build up inside the vacuum chamber. At the outset of the study, it was anticipated that electron cloud effects would limit the intensity of the positron ring, and that an instability associated with residual gas in the beam pipe would limit the intensity of the electron ring. It was also not clear whether the required very small beam size could be achieved. The results of this study are important contributions to the design of both the electron and positron damping rings in which all of those challenges are addressed and overcome. Our findings are documented in the ILC Technical Design Report, a document that represents the work of an international collaboration of scientists. Our contributions include design of the beam magnetic optics for the 3 km circumference damping rings, the vacuum system and surface treatments for electron cloud mitigation, the design of the guide field magnets, design of the superconducting damping wigglers, and new detectors for precision measurement of beam properties. Our study informed the specification of the basic design parameters for the damping rings, including alignment tolerances, magnetic field errors, and instrumentation. We developed electron cloud modelling tools and simulations to aid in the interpretation of the measurements that we carried out in the Cornell Electron-positron Storage Ring (CESR). The simulations provide a means for systematic extrapolation of our measurements at CESR to the proposed ILC damping rings, and ultimately to specify how the beam pipes should be fabricated in order to minimize the effects of the electron cloud. With the conclusion of this study, the design of the essential components of the damping rings is complete, including the development and characterization (with computer simulations) of the beam optics, specification of techniques for minimizing beam size, design of damping ring instrumentation, R&D into electron cloud suppression methods, tests of long term durability of electron cloud coatings, and design of damping ring vacuum system components.

43 PARTICLE ACCELERATORS↗
DOE OSTI2015

BES-HEP Connections: Common Problems in Condensed Matter and High Energy Physics, Round Table Discussion

On February 2, 2015 the Offices of High Energy Physics (HEP) and Basic Energy Sciences (BES) convened a Round Table discussion among a group of physicists on ‘Common Problems in Condensed Matter and High Energy Physics’. This was motivated by the realization that both fields deal with quantum many body problems, share many of the same challenges, use quantum field theoretical approaches and have productively interacted in the past. The meeting brought together physicists with intersecting interests to explore recent developments and identify possible areas of collaboration.... Several topics were identified as offering great opportunity for discovery and advancement in both condensed matter physics and particle physics research. These included topological phases of matter, the use of entanglement as a tool to study nontrivial quantum systems in condensed matter and gravity, the gauge-gravity duality, non-Fermi liquids, the interplay of transport and anomalies, and strongly interacting disordered systems. Many of the condensed matter problems are realizable in laboratory experiments, where new methods beyond the usual quasi-particle approximation are needed to explain the observed exotic and anomalous results. Tools and techniques such as lattice gauge theories, numerical simulations of many-body systems, and tensor networks are seen as valuable to both communities and will likely benefit from collaborative development.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2016

Transactive Control of Commercial Building HVAC Systems

This document details the development and testing of market-based transactive controls for building heating, ventilating and air conditioning (HVAC) systems. These controls are intended to serve the purposes of reducing electricity use through conservation, reducing peak building electric demand, and providing demand flexibility to assist with power system operations. This report is the summary of the first year of work conducted under Phase 1 of the Clean Energy and Transactive Campus Project. The methods and techniques described here were first investigated in simulation, and then subsequently deployed to a physical testbed on the Pacific Northwest National Laboratory (PNNL) campus for validation. In this report, we describe the models and control algorithms we have developed, testing of the control algorithms in simulation, and deployment to a physical testbed. Results from physical experiments support previous simulation findings, and provide insights for further improvement.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2019

LANSCE Diagnostic Robot Localization

Los Alamos Neutron Science Center (LANSCE) operates a linear particle accelerator (LINAC) that is used for a number of scientific research projects. Due to the presence of harmful radiation, researchers are not allowed in the beam tunnel during operation. Since the beam tunnel is inaccessible, an autonomous mobile robot is to be developed and deployed in the tunnel, monitoring the accelerator during operation. The robot will present real time data for operators and scientists from sensors such as a video camera, thermal camera, microphones, and muon detectors; allowing for beam diagnostics previously unavailable. Localization is a fundamental step in autonomous navigation of mobile robots, answering the “where am I” question. For this project, an Extended Kalman Filter (EKF) algorithm is implemented as a positional estimator. The EKF relies on an odometric motion model to predict the robot’s position and LIDAR measurement data to update the robot’s position. The measurement model is based on v features extracted from the LIDAR point cluster using the Split-and-Merge algorithm, and the nearest neighbor algorithm associates the features to an a priori feature map of the beam tunnel. The predicted and measured positions are then joined using a weighted value by means of the Kalman gain. The effectiveness of this localization technique is demonstrated using the LabVIEW robotics simulator.

42 ENGINEERING↗
DOE OSTI2020

Quasiparticle Couplings in Transport of Heat, Charge, and Spin for Novel Energy Materials. Final report

Understanding the microscopic processes involved in the transport and conversion of energy from the atomic-scale to the meso-scale is critical for the development of next-generation materials for energy conversion and information processing. The goal of this program was to elucidate the couplings between microscopic degrees-of-freedom of atomic vibrations, spins, and electrons, which underpin heat, charge, and spin transport. This project systematically investigated these quasi-particle interactions, using state-of-the-art neutron scattering techniques, combined with first-principles computer simulations. This research program uncovered new information and understanding, which helps to rationalize materials properties based on the interplay of their atomistic degrees of freedom.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Generation and Control of Self-Organized Nonlinear Kinetic Structures in High Energy Density Plasmas in the Presence of Intense Magnetic Fields and Ultrashort Laser Pulses

In the project we investigated mechanisms to sculpt phase space by controlling plasma instabilities. We found that linear theory, which applies in the initial growth phase of an instability, allows for initial conditions that can suppress instabilities. This provides a possible mechanism to release the energy available to an instability on demand. We developed various computational techniques that can reduce computational cost of simulations while maintaining or improving physical fidelity. We considered the Buneman instability in the presence of a ponderomotively driven plasma wave to examine the interplay between an instability and steady-state plasma response.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Learning a General Model of Single Phase Flow in Complex 3D Porous Media

Modeling effective transport properties of 3D porous media, such as permeability, at multiple scales is challenging as a result of the combined complexity of the pore structures and fluid physics—in particular, confinement effects which vary across the nanoscale to the microscale. While numerical simulation is possible, the computational cost is prohibitive for realistic domains, which are large and complex. Although machine learning (ML) models have been proposed to circumvent simulation, none so far has simultaneously accounted for heterogeneous 3D structures, fluid confinement effects, and multiple simulation resolutions. By utilizing numerous computer science techniques to improve the scalability of training, we have for the first time developed a general flow model that accounts for the pore-structure and corresponding physical phenomena at scales from Angstrom to the micrometer. Using synthetic computational domains for training, our ML model exhibits strong performance (R 2 = 0.9) when tested on extremely diverse real domains at multiple scales.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

A versatile approach to stabilize liquid-liquid interfaces using surfactant self-assembly

Stabilizing liquid–liquid interfaces, whether between miscible or immiscible liquids, is crucial for a wide range of applications, including energy storage, microreactors, and biomimetic structures. In this study, a versatile approach for stabilizing the water-oil interface is presented using the morphological transitions that occur during the self-assembly of anionic, cationic, and nonionic surfactants mixed with fatty acid oils. The morphological transitions underlying this approach are characterized and extensively studied through small-angle X-ray scattering (SAXS), rheometry, and microscopy techniques. Dissipative particle dynamics (DPD) as a simulation tool is adopted to investigate these morphological transitions both in the equilibrium ternary system as well as in the dynamic condition of the water-oil interface. Such a versatile strategy holds promise for enhancing applications such as liquid-in-liquid 3D printing. Moreover, it has the potential to revolutionize a wide range of fields where stabilizing liquid–liquid interfaces not only offers unprecedented opportunities for fine-tuning nanostructural morphologies but also imparts interesting practical features to the resulting liquid shapes. These features include perfusion capabilities, self-healing, and porosity, which could have significant implications for various industries.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Searching for Strongly Coupled Dark Sectors with Unsupervised and Generative Learning

Recipient of the URA Early Career Award for groundbreaking searches for dark matter arising from strongly coupled dark sectors with the CMS detector, pioneering work in ML-based model-independent anomaly detection for collider and astrophysics experiments, and leadership in the development of new AI/ML techniques to improve event reconstruction and detector simulation in particle physics, as well as novel strategies to accelerate AI inference and throughput with heterogeneous computing using coprocessors as a service.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Domain decomposition efforts in Chroma

Multilevel integration is a technique used in lattice quantum chromodynamics (LQCD) simulations, where the correlation functions are decomposed into factors that depend only on fields localized within specific lattice subdomains. The approach significantly improves the efficiency of the calculations because the factors can be independently integrated. The main challenge in implementing multilevel integration is that the standard formulation of the LQCD action is not local in the presence of fermions. However, past studies have shown that approximations of the quark propagator and the fermionic determinant, which depend on the gauge fields within specific subdomains, can still be effective. We will present the current progress in supporting domain decomposition within the Chroma software, which is necessary for implementing multilevel integration approaches. Most of the efforts have focused on extending the Chroma code base to efficiently manipulate subdomains for lattice fields and operators, as well as performing inversions and eigendecompositions within these domains.

Alcalde, Eloy Romero↗
DOE OSTI2024

Rational Design of High-Performing Electrodes in Energy Storage Devices

Rational design of interfaces with proper physico-chemical properties is necessary to optimize the performance of electrochemical devices, which requires fundamental understanding of the interfaces. In this project, we leveraged quantum mechanical and molecular dynamics simulations as well as machine learning (ML) technique to correlate the relationships between structure and properties including ion transport and electronic structures of cathode host materials in lithium-sulfur (Li-S) and carbon anode in sodium (Na) batteries for improved electrochemical performance.

25 ENERGY STORAGE↗
DOE OSTI2016

OSCILLATOR STRENGTHS OF VIBRIONIC EXCITATIONS OF NITROGEN DETERMINED BY THE DIPOLE (γ, γ) METHOD

The oscillator strengths of the valence-shell excitations of molecular nitrogen have significant applicational values in studies of the Earth's atmosphere and interstellar gases. In this work, the absolute oscillator strengths of the valence-shell excitations of molecular nitrogen in 12.3–13.4 eV were measured by the novel dipole (γ, γ) method, in which the high-resolution inelastic X-ray scattering is operated at a negligibly small momentum transfer and can simulate the photoabsorption process. Because the experimental technique used in the present work is distinctly different from those used previously, the present experimental results give an independent cross-check to previous experimental and theoretical data. The excellent coincidence of the present results with the dipole (e, e) and those that were extrapolated indicates that the present oscillator strengths can serve as benchmark data.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2026

Improving thermodynamic nudging in the E3SM Atmosphere Model version 2 (EAMv2): strategy and hindcast skills on weather systems

Nudging techniques are commonly employed to constrain atmospheric simulations toward observed states, facilitating model evaluation and sensitivity studies. However, if applied improperly – particularly to thermodynamic variables such as temperature and humidity – nudging can distort physical processes and introduce spurious biases, undermining the credibility of the simulations. This study presents an improved nudging implementation that applies vertically modulated tendencies to reduce adverse impacts on model physics. The framework is tested in version 2 of the Energy Exascale Earth System Model (EAMv2) using a suite of hindcast simulations nudged toward ERA5 reanalysis. We systematically evaluate the individual and combined effects of nudging wind, temperature, and humidity fields on the model's ability to represent large-scale atmospheric states and high-impact weather systems. Results show that the revised strategy – particularly when nudging temperature and humidity at selected levels – enhances hindcast skill by improving agreement with ERA5 without degrading the hydrological cycle or precipitation processes. Additional improvements in surface temperature, outgoing longwave radiation, and precipitation biases are achieved through targeted nudging of land-surface variables. The proposed approach strengthens the representation of large-scale conditions relevant to tropical cyclones, atmospheric rivers, and extratropical cyclones in the low-resolution EAMv2. These findings demonstrate that carefully designed thermodynamic nudging, especially of temperature and humidity, improves the realism of constrained simulations and broadens the utility of nudged EAMv2 for atmospheric modeling, machine learning, and high-impact weather research.

Atmospheric river↗
DOE OSTI2021

Unsupervised Resource Allocation with Graph Neural Networks

We present an approach for maximizing a global utility function by learning how to allocate resources in an unsupervised way. We expect interactions between allocation targets to be important and therefore propose to learn the reward structure for near-optimal allocation policies with a GNN. By relaxing the resource constraint, we can employ gradient-based optimization in contrast to more standard evolutionary algorithms. Our algorithm is motivated by a problem in modern astronomy, where one needs to select-based on limited initial information-among $10^9$ galaxies those whose detailed measurement will lead to optimal inference of the composition of the universe. Our technique presents a way of flexibly learning an allocation strategy by only requiring forward simulators for the physics of interest and the measurement process. We anticipate that our technique will also find applications in a range of resource allocation problems.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

Accurate and Timely Forecasts of Geologic Carbon Storage using Machine Learning Methods

Carbon capture and storage is one strategy to reduce greenhouse gas emissions. One approach to storing the captured CO2 is to inject it into deep saline aquifers. However, dynamics of the injected CO2 plume is uncertain and the potential for leakage back to the atmosphere must be assessed. Thus, accurate and timely forecasts of CO2 storage via real-time measurements integration becomes very crucial. This study proposes a learning-based, inverse-free prediction method that can accurately and rapidly forecast CO2 movement and distribution with uncertainty quantification based on limited simulation and observation data. The machine learning techniques include dimension reduction, multivariate data analysis, and Bayesian learning. The outcome is expected to provide CO2 storage site operators with an effective tool for real-time decision making.

Lu, Dan↗
DOE OSTI2025

Forecasting Dark Matter Subhalo Constraints from Stellar Streams using Implicit Likelihood Inference

The evidence for dark matter (DM) remains compelling, although attempts to understand its particle nature remain inconclusive. One promising method to study DM is detecting DM subhalos through their gravitational interactions with stellar streams. In this study, we apply Neural Posterior Estimation (NPE) to constrain subhalo interaction parameters, including mass, scale radius, velocity, and encounter geometry, from stellar stream kinematics. We generate particle spray simulations based on the Lagrange Cloud stripping technique, focusing on the ATLAS-Aliqa Uma stream as a test case. We train multiple NPE models across multiple observational scenarios, quantifying how kinematic completeness affects inference and forecasting constraints from upcoming surveys including LSST, 4MOST, and 10-year Gaia data. Our results demonstrate that NPE can produce accurate and well-calibrated posteriors. In the idealized case with full 6D coordinates, we achieve subhalo mass uncertainties of 15-20% for a $10^7 \, \mathrm{M_\odot}$ subhalo, with 5D coordinates (excluding radial velocities) achieving similar performance. Under realistic observational conditions, mass uncertainties range from 50% (present-day) to 20-40% (future scenarios), with comparable performance between the photometric-only LSST sample and a smaller sample that includes Gaia proper motions and 4MOST radial velocities. Most notably, we find that velocity bimodality emerges when phase space is poorly sampled, whether due to missing kinematic information or limited stellar tracers. Combining large photometric samples with targeted spectroscopic follow-up can effectively resolves this degeneracy. These results demonstrate the power of implicit likelihood inference for optimizing stellar stream observational strategies and forecasting DM subhalo constraints from upcoming surveys.

Nguyen, Tri [Northwestern U. (main); SkAI, Chicago↗