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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 1,153 records · Page 64
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Quadruple Langmuir probe characterization of different fuel gases in a plasma deflagration accelerator

Astrophysical flows may be studied by reproducing similar conditions using a coaxial plasma accelerator operating in the deflagration regime (or plasma deflagration accelerator). This allows for the recreation and investigation of dynamics present in complex highly coupled plasma systems at the laboratory scale. Here we report on measurements of the plasma density, temperature, plasma potential and velocity found using a quadruple Langmuir probe (QLP) on such a deflagration accelerator in the form of the Stanford Coaxial High ENerGy (CHENG) device operating with multiple gases – specifically argon, nitrogen and hydrogen. Experiments show a general decrease in bulk plasma velocity with gas atomic mass from upwards of 120 km s –1 with hydrogen to less than 30 km s –1 with argon. There was an accompanying increase in peak plasma density with increasing atomic mass from ~3 × 10 20 m –3 with hydrogen to ~1.5 × 10 21 m –3 with argon. It was found that the momentum flux and internal energy density also generally increase with atomic mass while the particle flux is constant between shots. Further investigation is needed to understand these correlations and the underlying physics. Lastly, comparisons with scaling laws show that while the CHENG device may be operated in such a way as to simulate the effects of bulk solar wind movement, it may not properly capture the thermal effects.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Physically and chemically smooth cesium-antimonide photocathodes on single crystal strontium titanate substrates

The performance of x-ray free electron lasers and ultrafast electron diffraction experiments is largely dependent on the brightness of electron sources from photoinjectors. Here, the maximum brightness from photoinjectors at a particular accelerating gradient is limited by the mean transverse energy (MTE) of electrons emitted from photocathodes. For high quantum efficiency (QE) cathodes like alkali-antimonide thin films, which are essential to mitigate the effects of non-linear photoemission on MTE, the smallest possible MTE and, hence, the highest possible brightness are limited by the nanoscale surface roughness and chemical inhomogeneity. In this work, we show that high QE Cs 3 Sb films grown on lattice-matched strontium titanate (STO) substrates have a factor of 4 smoother, chemically uniform surfaces compared to those traditionally grown on disordered Si surfaces. We perform simulations to calculate roughness induced MTE based on measured topographical and surface-potential variations on the Cs 3 Sb films grown on STO and show that these variations are small enough to have no consequential impact on the MTE and, hence, the brightness.

43 PARTICLE ACCELERATORS↗
DOE OSTI2025

A profile monitor for proton radiography experiments at the Los Alamos Neutron Science Center

The Proton Radiography (pRad) facility at the Los Alamos Neutron Science Center utilizes pulses of protons delivered by the 800 MeV linear accelerator to produce a series of radiographic images to study the dynamic behavior of materials under extreme conditions. Radiographs taken with an empty field of view, or beam pictures, are used to normalize transmission. However, because the center of the proton beam shifts between pulses, an in situ method for measuring beam position is required to normalize images for beam movement to perform absolute radiography. The beam profile monitor described here uses an array of scintillating fibers positioned in the beam path to produce light proportional to beam intensity across the beam cross section. This light is detected using fast photodiodes and a digital oscilloscope, providing a response time of several nanoseconds—suitable for measuring the 50-ns proton pulses used in pRad. The profile monitor achieves a measured position precision of 40 μm and an intensity precision of 0.7%, allowing for beam movement corrections to be applied to images, thereby improving data accuracy and image quality.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

Machine learning on FPGA for event selection

Real-time data processing is a frontier field in experimental particle physics. The application of FPGAs at the trigger level is used by many current and planned experiments (CMS, LHCb, Belle2, PANDA). Usually they use conventional processing algorithms. LHCb has implemented Machine Learning (ML) elements for real-time data processing with a triggered readout system that runs most of the ML algorithms on a computer farm. The work described in this article aims to test the ML-FPGA algorithms for streaming data acquisition. Herein, there are many experiments working in this area and they have a lot in common, but there are many specific solutions for detector and accelerator parameters that are worth exploring further. This report describes the purpose of the work and progress in evaluating the ML-FPGA application.

47 OTHER INSTRUMENTATION↗
DOE OSTI2021

Accelerating Ultrafast Spectroscopy with Compressive Sensing

We report ultrafast spectroscopy is an important tool for studying photoinduced dynamical processes in atoms, molecules, and nanostructures. Typically, the time to perform these experiments ranges from several minutes to hours depending on the choice of spectroscopic method. It is desirable to reduce this time overhead not only to shorten time and laboratory resources, but also to make it possible to examine fragile specimens that quickly degrade during long experiments. In this article, we motivate using compressive sensing to significantly shorten data acquisition time by reducing the total number of measurements in ultrafast spectroscopy. We apply this technique to experimental data from ultrafast transient absorption spectroscopy and ultrafast terahertz spectroscopy and show that good estimates can be obtained with as low as 15% of the total measurements, implying a sixfold reduction in the data acquisition time.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2026

Glauber-Theory Calculations of High-Energy Nuclear Scattering Observables Using Variational Monte Carlo Wave Functions

Experiments using intermediate- to high-energy radioactive nuclear beams present numerous findings. Extracting important properties of physical observables relies on a firm theoretical analysis. Though Glauber theory is believed to work well, no convincing calculation has so far been done. Here, we perform ab initio Glauber theory calculations of both elastic differential cross sections and total reaction cross sections for p+ 12 C, 12 C+ 12 C, and 6 He+ 12 C systems. The wave functions of both 6 He and 12 C are generated by variational Monte Carlo calculations with spatial and spin-isospin correlations induced by realistic two- and three-nucleon potentials. Glauber’s phase-shift function is computed by Monte Carlo integration up to all orders of nucleon-nucleon multiple scatterings. We show an excellent performance of the Glauber description to the selected data on the above systems. We also find that the cumulant expansion of the phase-shift function converges rapidly up to the second order for the above systems. This finding will open up interesting applications for the analysis of high-energy nuclear experiments.

Horiuchi, W. [Osaka Metropolitan University (Japan↗
DOE OSTI2022

Theory-guided experimental design in battery materials research

A reliable energy storage ecosystem is imperative for a renewable energy future, and continued research is needed to develop promising rechargeable battery chemistries. To this end, better theoretical and experimental understanding of electrochemical mechanisms and structure-property relationships will allow us to accelerate the development of safer batteries with higher energy densities and longer lifetimes. This Review discusses the interplay between theory and experiment in battery materials research, enabling us to not only uncover hitherto unknown mechanisms but also rationally design more promising electrode and electrolyte materials. We examine specific case studies of theory-guided experimental design in lithium-ion, lithium-metal, sodium-metal, and all-solid-state batteries. We also offer insights into how this framework can be extended to multivalent batteries. To close the loop, we outline recent efforts in coupling machine learning with high-throughput computations and experiments. Last, recommendations for effective collaboration between theorists and experimentalists are provided.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Solving challenges in QCD 3D partonic distributions

The superior luminosity and high polarization of CEBAF, combined with the high resolution and excellent particle identification capabilities of its detectors, as well as the ability for multidimensional and multiparticle detection using polarized targets, make Jefferson Lab uniquely positioned to disentangle the genuine intrinsic transverse structure of hadrons encoded in 3D partonic distributions—particularly in the kinematic regime dominated by valence quarks. The inclusion of Jefferson Lab data on semi-inclusive and hard exclusive hadron production has the potential to dramatically advance our understanding of non-perturbative QCD dynamics. Although a wealth of data from various Jefferson Lab experiments is already available, its incorporation into phenomenological studies has been slow, and a significant portion of data from other leptoproduction experiments is still missing from global fits. In this contribution, we discuss the existing challenges and outline a path forward for improving the analysis of low center-of-mass electroproduction experiments in general, and Jefferson Lab data in particular.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2019

Computation and consequences of high order amplitude- and parameter-dependent tune shifts in storage rings for high precision measurements

Nonlinear effects of the various electric field and magnetic field components of storage rings to confine the particles and bend their trajectory can cause substantial amplitude-dependent tune shifts within the beam. Furthermore, tune shifts are often sensitive to variations of system parameters, e.g. total particle momentum offsets $δp$. Such amplitude- and parameter-dependent tune shifts influence the dynamics and stability of a beam in particle storage rings. Thus, it is critical for high precision measurements to analyze and understand these influences. On this basis, we present in this paper normal form methods for the calculation of high order amplitude and system parameter dependencies of the horizontal and vertical tunes in storage rings using the differential algebra (DA) framework within COSY INFINITY. A storage ring is simulated using COSY INFINITY to generate a DA Poincaré return map describing the transverse phase space behavior after each revolution in the storage ring. The map is expanded around the parameter-dependent closed orbit of the system before transforming the resulting map into normal form coordinates to extract the high order tune dependencies on the phase space amplitude and variation in the system parameters. As a specific example, a storage ring similar to the Storage Ring of the Muon g-2 Experiment at Fermilab (E989) is investigated.

43 PARTICLE ACCELERATORS↗
DOE OSTI2024

Addressing the data and real-time challenges in large scale particle physics experiments through AI and in situ computing technologies

Modern high energy physics experiments are faced not only with the challenge of having to deal with extremely high data rates but with the need to process data quickly to meet real time constraints. At Fermilab, we explore the use of novel computing technologies and techniques to address these challenges. I will discuss my R&D efforts in applying such computing solutions to enhance the multi-messenger astronomy capabilities and improve the overall physics performance of large-scale LArTPC based neutrino experiments. These efforts offer excellent opportunities for fruitful collaboration.

43 PARTICLE ACCELERATORS↗
DOE OSTI2021

Fracture Network Localization Preceding Catastrophic Failure in Triaxial Compression Experiments on Rocks

We quantify the spatial distribution of fracture networks throughout six in situ X-ray tomography triaxial compression experiments on crystalline rocks at confining stresses of 5–35 MPa in order to quantify how fracture development controls the final macroscopic failure of the rock, a process analogous to those that control geohazards such as earthquakes and landslides. Tracking the proportion of the cumulative volume of fractures with volumes >90th percentile to the total fracture volume, ∑ v 90 / v t o t indicates that the fracture networks tend to increase in localization toward these largest fractures for up to 80% of the applied differential stress. The evolution of this metric also matches the evolution of the Gini coefficient, which measures the deviation of a population from uniformity. These results are consistent with observations of localizing low magnitude seismicity before large earthquakes in southern California. In both this analysis and the present work, phases of delocalization interrupt the general increase in localization preceding catastrophic failure, indicating that delocalization does not necessarily indicate a reduction of seismic hazard. However, the proportion of the maximum fracture volume to the total fracture volume does not increase monotonically. Experiments with higher confining stress tend to experience greater localization. To further quantify localization, we compare the geometry of the largest fractures, with volumes >90th percentile, to the best fit plane through these fractures immediately preceding failure. The r 2 scores and the mean distance of the fractures to the plane indicate greater localization in monzonite than in granite. The smaller mean mineral diameter and lower confining stress in the granite experiments may contribute to this result. Tracking these various metrics of localization reveals a close association between macroscopic yielding and the acceleration of fracture network localization. Near yielding, ∑ v 90 / v t o t and the Gini coefficient increase while the mean distance to the final failure plane decreases. Macroscopic yielding thus occurs when the rate of fracture network localization increases.

58 GEOSCIENCES↗
DOE OSTI2021

Seeding Supermassive Black Holes with Self-interacting Dark Matter: A Unified Scenario with Baryons

Observations show that supermassive black holes (SMBHs) with a mass of ~10 9 M ⊙ exist when the universe is just 6% of its current age. We propose a scenario where a self-interacting dark matter halo experiences gravothermal instability and its central region collapses into a seed black hole. The presence of baryons in protogalaxies could significantly accelerate the gravothermal evolution of the halo and shorten collapse timescales. The central halo could dissipate its angular momentum remnant via viscosity induced by the self-interactions. The host halo must be on high tails of density fluctuations, implying that high-z SMBHs are expected to be rare in this scenario. We further derive conditions for triggering general relativistic instability of the collapsed region. Furthermore, our results indicate that self-interacting dark matter can provide a unified explanation for diverse dark matter distributions in galaxies today and the origin of SMBHs at redshifts z ~ 6–7.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

FEL2026 - 42nd International Free Electron Laser Conference - Prepress

On behalf of the International Executive Committee of the FEL Conference series, we are pleased to announce the 42nd International Free Electron Laser Conference (FEL2026). The conference will be held at Li Ka Shing Center located on Stanford campus from August 23rd to August 28th, 2026. FEL2026 will focus on recent advances in free electron laser theory and experiments, electron beam, photon beam and undulator technologies, and applications of free electron lasers. FEL2026 will be hosted by SLAC National Accelerator Laboratory and Stanford PULSE Institute. Stanford is the birthplace of the free-electron laser. SLAC houses two premier X-ray FEL facilities (LCLS and LCLS‑II) in the US. The conference program will include an optional tour of the LCLS and LCLS-II. Stay tuned for more conference information by following this official conference website (www.fel2026.org). Email questions should be addressed to fel2026@slac.stanford.edu.

Summers, Tasha [SLAC National Accelerator Laborato↗
DOE OSTI2020

Generation of High-Charge Magnetized Electron Beams Consistent With JLEIC Electron Cooling Requirements

The proposed Jefferson Lab Electron-Ion Collider (JLEIC), currently under design, relies on electron cooling in order to achieve the desired luminosity. This includes an electron beam with >55 Mev, 3.2 nC bunches that cools hadron beams with energies up to 100 GeV. To enhance the cooling, the electron beam must be magnetized with a specific eigen-emittance partition. This paper explores the use of the Fermilab Accelerator Science and Technology (FAST) facility to demonstrate the generation of an electron beam with parameters consistent with those required in the JLEIC high-energy cooler. We demonstrate via simulations the generation of the required electron-beam parameters and perform a preliminary experiment to validate FAST capabilities to produce such beams.

43 PARTICLE ACCELERATORS↗
DOE OSTI2023

Multi-scale fission product release model with comparison to AGR data

TRistructural ISOtropic (TRISO) particle fuel is central to several advanced, high-temperature reactor designs. Each particle consists of a fuel kernel encapsulated by three layers of carbon and ceramics that prevent the release of fission products and ensure physical integrity. Despite outstanding retention properties, fission product release has been observed from intact particles. To better understand and quantify fission product release from TRISO particles, a multiscale, mechanistic model of fission product transport is being developed by the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program. Previous work focused on silver (Ag) transport and improved Ag release predictions. The work described in this report builds on this experience to better understand cesium (Cs) transport in silicon carbide (SiC), the main barrier to the release of fission products. Atomistic simulations provide bulk and grain boundary (GB) Cs diffusivities in SiC, which are used by phase field simulations in the mesoscale code Marmot to determine the temperature, microstructure, and irradiation-dependent Cs diffusivity at the mesoscale in SiC. This approach attributes the different temperature regimes experimentally observed for Cs diffusivities in SiC to a transition from bulk-dominated diffusivity at high temperatures to a GB-dominated regime at low temperatures, providing new insight. The multiscale, mechanistic effective diffusivity is then implemented in the fuel performance code BISON and further validated by comparing Cs release predictions from Advanced Gas Reactor (AGR)-1 and AGR-2 post-irradiation measurements. The new model improves BISON’s predictability. This document also reports improvements made on Ag transport modeling by accounting for different GB types having different diffusivities. Moreover, this report details preliminary efforts to model palladium (Pd) attack of the SiC at the mesoscale using a phase field approach. Pd attack and its impact on accelerated Ag transport remains a misunderstood phenomenon, and we use the model to demonstrate that the formation of lamellae that has been observed in experiments can be explained by the reaction of Pd with SiC to form alternating layers of graphite and Pd 2 Si. This effort aims to improve our understanding of the reaction and eventually provide a model for BISON to account for Pd penetration and its effects on fission product release.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2020

Calibration of CDM-Based Creep Constitutive Model Using Accelerated Creep Test (ACT) Data

In conventional creep testing (CCT) a specimen is subject to constant load and temperature for a long-duration until creep rupture occurs. Conventional testing can be costly when considering the number of experiments needed to characterize the creep response of a material over a range of stress and temperature. To predict long-term creep-rupture properties, the time-temperature-stress superposition principle (TTSSP) approach has been employed where stress and/or temperature is applied at an elevated level; the result of which are extrapolated down to low stress and/or temperature conditions. These methods have been successful in predicting minimum-creep-strain-rate (MCSR) and stress-rupture (SR) but suffer from an inability to predict the creep deformation curve or account for changes in deformation mechanisms or aging that occurs at long-duration. An accelerated technique, termed the Stepped isostress method (SSM) allows the accelerated testing of materials to determine their creep deformation response. Unlike TTSSP tests, the SSM test employs a single specimen where the stress is periodically step increased until rupture. The SSM creep deformation curve is processed (time and strain shifted) to produce an accelerated creep deformation curve that represent the creep deformation curve at the initial stress level in SSM. A processing procedure for metals has yet to be developed. The research objective of this study is to develop a processing procedure for SSM test data using a creep-damage constitutive model. Triplicate SSM tests were conducted on Ni-based superalloy Inconel 718 at 650°C with stress being periodically increased until rupture. Triplicate CCT tests were conducted at the initial stress level of the SSM tests. The Sine-hyperbolic (Sinh) creep-damage model was employed in this study. The Sinh creep-damage constitutive model is based on coupled creep strain rate and damage evolution equations; where both rates are dependent on the current state of damage. Calibration is two-step: analytical and numerical optimization. Each stepped creep deformation curve is tackled quasi-analytically to determine MCSR and SR related material constants and accumulated damage. The damage accumulated at the end of each step was then passed onto subsequent steps to calibrate the MCSR, rupture prediction, and damage evolution. Numerical optimization was applied to optimize model constants involved in the creep strain constitutive equations in order to generate best-fitted Sinh creep deformation curves. The Sinh model predictions were compared to the SSM and CCT data. The Sinh model satisfactorily predicts the SSM data and thus the calibrated material constants provides a good estimate of rupture found in the CCT data. Calibration using SSM data reduces the number of tests needed to calibrate a model; significantly reducing costs. A single SSM test replaces numerous creep tests at different stresses.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Convolutional neural network based non-iterative reconstruction for accelerating neutron tomography *

Abstract Neutron computed tomography (NCT), a 3D non-destructive characterization technique, is carried out at nuclear reactor or spallation neutron source-based user facilities. Because neutrons are not severely attenuated by heavy elements and are sensitive to light elements like hydrogen, neutron radiography and computed tomography offer a complementary contrast to x-ray CT conducted at a synchrotron user facility. However, compared to synchrotron x-ray CT, the acquisition time for an NCT scan can be orders of magnitude higher due to lower source flux, low detector efficiency and the need to collect a large number of projection images for a high-quality reconstruction when using conventional algorithms. As a result of the long scan times for NCT, the number and type of experiments that can be conducted at a user facility is severely restricted. Recently, several deep convolutional neural network (DCNN) based algorithms have been introduced in the context of accelerating CT scans that can enable high quality reconstructions from sparse-view data. In this paper, we introduce DCNN algorithms to obtain high-quality reconstructions from sparse-view and low signal-to-noise ratio NCT data-sets thereby enabling accelerated scans. Our method is based on the supervised learning strategy of training a DCNN to map a low-quality reconstruction from sparse-view data to a higher quality reconstruction. Specifically, we evaluate the performance of two popular DCNN architectures—one based on using patches for training and the other on using the full images for training. We observe that both the DCNN architectures offer improvements in performance over classical multi-layer perceptron as well as conventional CT reconstruction algorithms. Our results illustrate that the DCNN can be a powerful tool to obtain high-quality NCT reconstructions from sparse-view data thereby enabling accelerated NCT scans for increasing user-facility throughput or enabling high-resolution time-resolved NCT scans.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗