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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 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Continuum Correlations from CFD-DEM Modeling of Conduction Heat Transfer in Granular Flows

Heat transfer between a surface and flowing particles is analyzed to improve the accuracy of continuum models for wall-to-bed heat transfer in a fluidized bed. Discrete element modeling (DEM) is used to model a fluidized bed heat exchanger where heat enters the system through a heated wall. The DEM heat transfer predictions are validated against published experimental work (Brewster et al., 2024) with less than 15% error. In previous work by Morris et al. (2015), a continuum model was developed using data from high-fidelity DEM simulations of chute flows. In the current study, the continuum model is extended and validated for fluidized beds. The sensitivity of the continuum heat transfer model parameters, which was not quantified in previous studies, is also investigated. It is observed that for a given particle with specific properties, e.g. the particle size, roughness, and conduction lens radius, the continuum correlation developed for heat transfer from a heated boundary to the particle bed depends mainly on the solid fraction or porosity of the particle bed for a given fluid. The new continuum heat transfer model is then validated over a wide range of superficial velocities via comparisons to both discrete element and experimental data. It is shown that this correlation is valid for a large range of particle flow conditions from chute flows to fluidized beds with less than 10% error as compared to DEM predictions.

14 SOLAR ENERGY↗
DOE OSTI2022

Photon detector response function methodology using MCNP and shift hybrid radiation transport code for wide-area contamination assay applications

Here, radiation transport modeling using the Monte Carlo N-Particle (MCNP) radiation transport code and Monte Carlo code, Shift, were employed to model detector responses for a variety of wide-area photon contamination scenarios. In this study, 2" × 2" and 3" × 3" cylindrical NaI(Tl) scintillation detector configurations at source detector-distances of 0.5 cm, 1 cm, 2.54 cm, 10 cm, and 30 cm were modeled. Media of soil, concrete, and steel were evaluated for contamination depths ranging from surface to a depth of an infinite thickness in each medium for photon energies ranging from 20 keV to 3 MeV, which correspond to the energies that current detectors can discern. Monoenergetic photon surface contamination detector responses for each of the media, source–detector distances, and detectors were estimated using MCNP v6.2. Shift was harnessed for improved variance reduction of particle transport in highly attenuating media to obtain average cell fluxes in the two MCNP NaI(Tl) scintillation detector configurations. Average cell flux values in Shift were coupled with detector responses from MCNP to convert average cell flux in a void to energy distribution of pulses in the NaI(Tl) scintillation detector crystal of interest. An optimized detector response function methodology was developed by coupling the MCNP radiation transport method with the Consistent Adjoint Driven Importance Sampling (CADIS) hybrid radiation transport method built into Shift to significantly decrease the runtime of thousands of MCNP pulse height simulations. The methodology may be utilized to quickly and accurately facilitate the assessment of a broad range of wide-area environmental contamination assay and decommissioning cleanup applications.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2020

AGR-2 Loose Particle Heating Tests in the Furnace for Irradiated TRISO Testing

A furnace system was developed to thermally expose individual tristructural-isotropic (TRISO) coated particles to expand upon established postirradiation examination (PIE) safety testing that is used to explore particle failures and fission product release from compacts. Two systems were installed in the Irradiated Fuels Examination Facility (IFEL) at Oak Ridge National Laboratory (ORNL). The targeted design was intended to be simple and flexible to allow a range in conditions to be explored. Initial inert atmosphere testing indicated the presence of particle failures, so modifications to the testing approach were implemented to improve the furnace operation. Ultimately, burnback particles were analyzed to provide a direct measurement of fission product release, thus avoiding the complications from integral release that were observed during whole compact testing. Particles were exposed to temperatures ranging 1,150–1,300°C for up to 1,500 h and 1,600°C up to 500 h. No indication of uniform release of fission products such as 106 Ru, 125 Sb, or 154 Eu was observed, however, indication of particle dependent 154 Eu release was suggested for select particles. Exploration of 110m Ag release was limited to 1,150°C and 1,300°C up to 500 h. The analysis indicated that there was nonuniform release of 110m Ag and supports a possible bimodal temperature dependence on silver release.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

Multiple emission components in the Cygnus cocoon detected from Fermi -LAT observations

Star-forming regions may play an important role in the life cycle of Galactic cosmic rays (CRs), notably as home to specific acceleration mechanisms and transport conditions. Gamma-ray observations of Cygnus X have revealed the presence of an excess of hard-spectrum gamma-ray emission, possibly related to a cocoon of freshly accelerated particles. We seek an improved description of the gamma-ray emission from the cocoon using ~13 yr of observations with the Fermi-Large Area Telescope (LAT) and use it to further constrain the processes and objects responsible for the young CR population. We developed an emission model for a large region of interest, including a description of interstellar emission from the background population of CRs and recent models for other gamma-ray sources in the field. Thus, we performed an improved spectro-morphological characterisation of the residual emission including the cocoon. The best-fit model for the cocoon includes two main emission components: an extended component FCES G78.74+1.56, described by a 2D Gaussian of extension r 68 = 4.4° ± 0.1° -0.1° +0.1° and a smooth broken power law spectrum with spectral indices 1.67 ± 0.05 -0.01 +0.02 and 2.12 ± 0.02 -0.01 +0.00 below and above 3.0 ± 0.6 -0.2 +0.0 GeV, respectively; and a central component FCES G80.00+0.50, traced by the distribution of ionised gas within the borders of the photo-dissociation regions and with a power law spectrum of index 2.19 ± 0.03 -0.01 +0.00 that is significantly different from the spectrum of FCES G78.74+1.56. An additional extended emission component FCES G78.83+3.57, located on the edge of the central cavities in Cygnus X and with a spectrum compatible with that of FCES G80.00+0.50, is likely related to the cocoon. For the two brightest components FCES G80.00+0.50 and FCES G78.74+1.56, spectra and radial-azimuthal profiles of the emission can be accounted for in a diffusion-loss framework involving one single population of non-thermal particles with a flat injection spectrum. Particles span the full extent of FCES G78.74+1.56 as a result of diffusion from a central source, and give rise to source FCES G80.00+0.50 by interacting with ionised gas in the innermost region. For this simple diffusion-loss model, viable setups can be very different in terms of energetics, transport conditions, and timescales involved, and both hadronic and leptonic scenarios are possible. The solutions range from long-lasting particle acceleration, possibly in prominent star clusters such as Cyg OB2 and NGC 6910, to a more recent and short-lived release of particles within the last 10–100 kyr, likely from a supernova remnant. The observables extracted from our analysis can be used to perform detailed comparisons with advanced models of particle acceleration and transport in star-forming regions.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Machine Learning for Anomaly Detection in Neural Network Security and SRF Cavities

This dissertation explores the development and deployment of machine learning approaches to address critical challenges in anomaly detection across two distinct domains: neural network security in federated learning settings and cavity behavior analysis in particle accelerator operations at Jefferson Lab in Newport News, Virginia. Anomaly detection identifies deviations from expected patterns, safeguarding systems in cybersecurity, industry, and research against malicious activities and failures. This dissertation demonstrates how our machine learning approaches enhance detection accuracy and efficiency in both neural network security and industrial applications. First, we investigate vulnerabilities in deep neural networks deployed in federated learning. Although federated learning preserves user privacy by training models locally, it remains vulnerable to backdoor attacks, in which malicious participants embed hidden triggers that induce targeted misbehavior. We propose a self-supervised contrastive learning framework to detect and mitigate such backdoor attacks. In our experiments, this method achieves higher detection accuracy and lower false positive rates than existing defenses, while operating without access to local model updates or original training data and thus preserving the privacy guarantees of the federated setting. Second, we address the operational reliability of superconducting radio-frequency (SRF) cavities at the Continuous Electron Beam Accelerator Facility (CEBAF). Our research leverages an unsupervised learning approach, combined with Principal Component Analysis (PCA) and k-means clustering, to identify anomalous behaviors in SRF cavities. Our method detects subtle anomalous behavior by analyzing SRF signal data. This knowledge allows for the early detection and resolution of potential faults, significantly improving the efficiency and reliability of operations. Third, we extend these insights to time-series anomaly detection more broadly. We design a contrastive-learning based model tailored to increasingly dynamic environments and academic research. This model improves detection accuracy in settings that require real-time monitoring and predictive maintenance. Our research underscores the broader applicability and impact of advanced machine learning techniques in anomaly detection. By extracting meaningful patterns from complex data, machine learning can significantly enhance security in distributed neural networks and improve the efficiency of particle accelerator operations. This dissertation serves as a stepping stone for future investigations into the vast possibilities of anomaly detection, inspiring further exploration and development of machine learning techniques in this field.

Ferguson, Hal [Old Dominion University]↗
DOE OSTI2020

Improving inference with matrix elements and machine learning

Particle physics processes bring together a high-energy amplitude described by quantum field theory and nonperturbative effects and detector interactions described by complex computer simulations. We review some recently developed multivariate inference techniques that leverage this structure and combine matrix-element information with machine learning. Automated by the MadMiner package, the new techniques have been applied to multiple problems in particle physics, allowing for stronger limits than traditional analysis methods and showing their potential to improve the sensitivity of the LHC legacy measurements.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2020

Calibration of the charge and energy loss per unit length of the MicroBooNE liquid argon time projection chamber using muons and protons

In this paper, we describe a method used to calibrate the position- and time-dependent response of the MicroBooNE liquid argon time projection chamber anode wires to ionization particle energy loss. The method makes use of crossing cosmic-ray muons to partially correct anode wire signals for multiple effects as a function of time and position, including cross-connected TPC wires, space charge effects, electron attachment to impurities, diffusion, and recombination. The overall energy scale is then determined using fully-contained beam-induced muons originating and stopping in the active region of the detector. Using this method, we obtain an absolute energy scale uncertainty of 2% in data. We use stopping protons to further refine the relation between the measured charge and the energy loss for highly-ionizing particles. This data-driven detector calibration improves both the measurement of total deposited energy and particle identification based on energy loss per unit length as a function of residual range. As an example, the proton selection efficiency is increased by 2% after detector calibration.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

Enhanced Methanol Synthesis from CO 2 Hydrogenation Achieved by Tuning the Cu–ZnO Interaction in ZnO/Cu 2 O Nanocube Catalysts Supported on ZrO 2 and SiO 2

The nature of the Cu–Zn interaction and especially the role of Zn in Cu/ZnO catalysts used for methanol synthesis from CO 2 hydrogenation are still debated. Migration of Zn onto the Cu surface during reaction results in a Cu–ZnO interface, which is crucial for the catalytic activity. However, whether a Cu–Zn alloy or a Cu–ZnO structure is formed and the transformation of this interface under working conditions demand further investigation. Here, ZnO/Cu 2 O core–shell cubic nanoparticles with various ZnO shell thicknesses, supported on SiO 2 or ZrO 2 were prepared to create an intimate contact between Cu and ZnO. The evolution of the catalyst’s structure and composition during and after the CO 2 hydrogenation reaction were investigated by means of operando spectroscopy, diffraction, and ex situ microscopy methods. The Zn loading has a direct effect on the oxidation state of Zn, which, in turn, affects the catalytic performance. High Zn loadings, resulting in a stable ZnO catalyst shell, lead to increased methanol production when compared to Zn-free particles. Low Zn loadings, in contrast, leading to the presence of metallic Zn species during reaction, showed no significant improvement over the bare Cu particles. Therefore, our work highlights that there is a minimum content of Zn (or optimum ZnO shell thickness) needed to activate the Cu catalyst. Furthermore, in order to minimize catalyst deactivation, the Zn species must be present as ZnO x and not metallic Zn or Cu–Zn alloy, which is undesirably formed during the reaction when the precatalyst ZnO overlayer is too thin.

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

Structural and chemical evolutions of a magnesium vanadium oxide cathode under electrochemical cycling in magnesium batteries

The design of cathode materials that remain chemically and structurally stable during repetitive ion insertion and extraction poses a significant challenge in developing multivalent batteries. The cycling stability of traditional metal oxide-based cathode is challenged by sluggish diffusion of multivalent cations and parasitic reactivity at interfacial regimes, including the cathode electrolyte interphase layer (CEI). Understanding the reactions at the cathode-electrolyte interface, particularly those induced by non-stoichiometric surface layers, is a crucial design parameter for both cathode materials and electrolytes. Here, in this study, we employed multimodal analysis, including in situ and ex situ X-ray photoelectron spectroscopy (XPS), high resolution transmission electron microscopy (TEM) and electrochemical impedance spectroscopy (EIS) to examine the surface reactions and subsequent structural and chemical evolutions of the CEI on high voltage magnesium vanadium oxide (MgV 2 O 4 ) spinel cathode during the Mg 2+ insertion/extraction processes. The results revealed that the presence of non-stoichiometric surface layers in the magnesium vanadium oxide cathode drive the decomposition of bis(trifluoromethanesulfonyl)imide (TFSI - ) anion, leading to the formation of the CEI layer. The CEI layer could inhibit the Mg 2+ ion transfer processes. Accompanying this reactivity-driven degradation, the magnesium vanadium oxide cathode undergoes pulverization, forming clusters of nanosized particles. This process likely improves cycling ability by creating new intercalation sites and shortening the diffusion pathway for the Mg 2+ cations. This study demonstrates that controlling surface stoichiometry and engineering morphological properties are critical design parameters for high performance cathodes for multivalent batteries.

25 ENERGY STORAGE↗
DOE OSTI2022

Weather aging effects on modified asphalt with rubber-polyethylene composites

Weather aging may cause more severe degradation on asphalt than thermal-oxidative aging due to the synergistic effect among oxygen, heat, ultraviolet (UV) radiation, and moisture. This study aimed to investigate weather aging effects and anti-aging mechanisms on asphalt modified with rubber-polyethylene (PE) composites. The modified binder blends and asphalt mixtures were subjected to outdoor weather aging. Dynamic shear rheometer (DSR), Fourier transform infrared spectroscopy (FTIR), Gel permeation chromatography (GPC), and optical microscopy tests were adopted to characterize the rheological properties, aging resistance, polymer degradation, and anti-aging mechanisms of modified binder blends, respectively. Mixture performance tests including Asphalt Pavement Analyzer (APA) and Ideal-CT tests were used to evaluate rutting and cracking resistance of asphalt mixtures. Results showed that weather aging can cause more severe aging to asphalt binders than pressure aging vessel (PAV) due to the severe degradation of PE particles. Rubber-PE composites alloyed with an extruder proved to stabilize PE particles in asphalt and significantly improve the aging resistance of modified binder blends. Furthermore, the enhanced aging resistance is attributed to the dispersion of PE particles and carbon black released by soluble rubbers.

Aging resistance↗
DOE OSTI2021

Characterization of hot-pressed von Alpen type NASICON ceramic electrolytes

The Na-ion conducting solid electrolyte NASICON is a promising solid state electrolyte (SSE) for use in Na based electrochemical systems. The effects of particle morphology and synthesis of von Alpen type NASICON via hot-pressing were investigated. Spray dried particles were shown to improve mechanical and electrochemical properties. X-ray diffraction, scanning electron microscopy, impulse excitation measurements, Vickers hardness, and impedance spectroscopy were used to correlate relationships between phase purity, microstructure, mechanical properties, and electrochemical properties. Scanning electron microscopy showed the presence of a glass phase as between 19.08% and 28.23% area percentage and a ZrO 2 phase between 0.46% and 3.51% area percentage in the hot-pressed samples. Impulse excitation showed elastic modulus varying from 83.65 to 97.65 GPa. The first values of Poisson's ratio and shear modulus of NASICON are reported as between 0.23 and 0.26 and 33.87 to 38.79 GPa, respectively. Vickers hardness and fracture toughness measurements showed Vickers hardness ranging from 4.30 to 4.68 GPa and fracture toughness ranging from 1.05 to 1.09 MPa m ½ . Impedance spectroscopy showed grain conductivities ranging from 1.023 to 1.287 mS/cm, with grain boundary resistance percentages between 73.22 and 47.5%. Total conductivities ranged from 0.292 to 0.596 mS/cm, with 0.596 mS/cm being achieved at room temperature for the spray dried powders with lower grain boundary resistance percentages.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Synthetic antibodies against BRIL as universal fiducial marks for single-particle cryoEM structure determination of membrane proteins

We propose the concept of universal fiducials based on a set of pre-made semi-synthetic antibodies (sABs) generated by customized phage display selections against the fusion protein BRIL, an engineered variant of apocytochrome b562a. These sABs can bind to BRIL fused either into the loops or termini of different GPCRs, ion channels, receptors and transporters without disrupting their structure. A crystal structure of BRIL in complex with an affinity-matured sAB (BAG2) that bound to all systems tested delineates the footprint of interaction. Negative stain and cryoEM data of several examples of BRIL-membrane protein chimera highlight the effectiveness of the sABs as universal fiducial marks. Taken together with a cryoEM structure of sAB bound human nicotinic acetylcholine receptor, this work demonstrates that these anti-BRIL sABs can greatly enhance the particle properties leading to improved cryoEM outcomes, especially for challenging membrane proteins.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Fluid and gyrokinetic turbulence in open field-line, helical plasmas

Two-fluid Braginskii codes have simulated open-field line turbulence for over a decade, and only recently, it has become possible to study these systems with continuum gyrokinetic codes. This work presents a first-of-its-kind comparison between fluid and (long-wavelength) gyrokinetic models in open field-lines, using the GDB and Gkeyll codes to simulate interchange turbulence in the Helimak device at the University of Texas [T. N. Bernard et al., Phys. Plasmas 26, 042301 (2019)]. Partial agreement is attained in a number of diagnostic channels when the GDB sources and sheath boundary conditions (BCs) are selected carefully, especially the heat-flux BCs that can drastically alter the temperature. The radial profile of the fluctuation levels is qualitatively similar and quantitatively comparable on the low-field side, although statistics such as moments of the probability density function and the high-frequency spectrum show greater differences. This comparison indicates areas for future improvement in both simulations, such as sheath BCs, and improvements in GDB like particle conservation and spatially varying thermal conductivity, in order to achieve better fluid-gyrokinetic agreement and increase fidelity when simulating experiments.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Exotic Meson Photoproduction at GlueX – Search for the hybrid candidate Y

Understanding the hadron spectrum is one of the primary goals of non-perturbative QCD. Many predictions have experimentally been confirmed, others still remain under experimental investigation. Of particular interest is how gluonic excitations give rise to states with constituent glue. One class of such states are hybrid mesons that are predicted by theoretical models and Lattice QCD calculations. Searching for and understanding the nature of these states is a primary physics goal of the GlueX experiment at the CEBAF accelerator at Jefferson Lab. A search for a JPC = 1-- hybrid meson candidate, the Y (2175), in phi(1020)pi+pi+ and phi(1020)f0(980) channels in photoproduction on a proton target has been conducted. A first measurement of non-resonant phi(1020)pi+pi+ and phi(1020)f0(980) total cross sections in photoproduction has been performed. An upper limit on the resonance production cross section for the Y (2175) -> phi(1020)pi+pi+ and Y (2175) -> phi(1020)f0(980) channels are estimated. Since the analysis essentially depends on the quality of the charged kaon identification, also an optimization of particle identification through an improvement of the energy loss estimation in the CDC by a truncated mean method has been investigated.

Hamdi, Abdennacer↗
DOE OSTI2021

Secondary Aerosol Formation in an Arctic Oil Field (Campaign Report)

Atmospheric aerosols contribute significantly to arctic warming, yet significant differences in aerosol concentration levels and seasonal cycles often exist between models and observations. Recent studies of cloud properties across the North Slope of Alaska show the significant, regional influence of oil field emissions. Development across the Arctic motivates the need to characterize these oilfield emissions to further predict their roles in changing future arctic climate. Our previous August-September 2016 Atmospheric Radiation Measurement (ARM) user facility field campaign resulted in improved understanding of atmospheric particles emitted within the North Slope of Alaska (NSA) oil fields, as well as the aging of sea spray aerosol. Following Polar Sunrise during arctic spring, chlorine chemistry is active, and we hypothesize that oxidation of oil field hydrocarbons by chlorine atoms (Cl) generates oxygenated volatile organic compounds (OVOCs) leading to springtime arctic secondary organic aerosol (SOA) formation.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

3D-Reconstruction of Tau Neutrinos in LArTPC Detectors

The Deep Underground Neutrino Experiment (DUNE) is a next-generation neutrino experiment currently under construction. DUNE will consist of two high-resolution neutrino interaction imaging detectors exposed to the world’s most intense neutrino beam, with the Near Detector at Fermilab and the Far Detector 1,300 km away in the Sanford Underground Research Facility in South Dakota, US. The high statistics and excellent resolution capabilities of DUNE's $^{40}$Ar detector will allow us to make precision studies of oscillation parameters capable of searching for CP violation in the lepton sector, testing interaction models, and studying phenomena that have until now, seemed too complex to measure, like $\nu_\tau$ detection and therefore, providing the completion of the 3-flavor neutrino paradigm. Knowledge of the $\nu_\tau$ detection can impact a broad spectrum of open questions. These include searching for non-standard neutrino interactions, constraining the unitarity of the PMNS matrix, searching for sterile neutrinos, and studying neutrino interactions. In the case of LArTPC data, the detector hits can be considered nodes in a graph, and the edges represent the spatial and temporal relationships between them. By using graph neural networks, it is possible to exploit these relationships and improve the accuracy of particle identification and reconstruction. During my presentation and specifically for tau neutrino reconstruction, I will show the effectiveness and reliability of our in-house developed graph neural network (GNN), NuGraph. This GNN classifies detector hits based on the particle type responsible for their production, assuring that the system accurately identifies and categorizes information based on its unique characteristics.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

HERMES-400 Microcalorimetry Measurements of Nuclear Fuel at Idaho National Laboratory

Microcalorimetry updates from HERMES-400 located at Idaho National Laboratory will be presented. In particular, the current outlook as well as future upgrades will be discussed. Data will be presented for Byron and TRISO particle fuel measurements highlighting improved energy resolution compared to traditional gamma-ray spectroscopy.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗