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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 1,333 records · Page 74
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

DefectTrack: a deep learning-based multi-object tracking algorithm for quantitative defect analysis of in-situ TEM videos in real-time

Abstract In-situ irradiation transmission electron microscopy (TEM) offers unique insights into the millisecond-timescale post-cascade process, such as the lifetime and thermal stability of defect clusters, vital to the mechanistic understanding of irradiation damage in nuclear materials. Converting in-situ irradiation TEM video data into meaningful information on defect cluster dynamic properties (e.g., lifetime) has become the major technical bottleneck. Here, we present a solution called the DefectTrack , the first dedicated deep learning-based one-shot multi-object tracking (MOT) model capable of tracking cascade-induced defect clusters in in-situ TEM videos in real-time. DefectTrack has achieved a Multi-Object Tracking Accuracy (MOTA) of 66.43% and a Mostly Tracked (MT) of 67.81% on the test set, which are comparable to state-of-the-art MOT algorithms. We discuss the MOT framework, model selection, training, and evaluation strategies for in-situ TEM applications. Further, we compare the DefectTrack with four human experts in quantifying defect cluster lifetime distributions using statistical tests and discuss the relationship between the material science domain metrics and MOT metrics. Our statistical evaluations on the defect lifetime distribution suggest that the DefectTrack outperforms human experts in accuracy and speed.

42 ENGINEERING↗
DOE OSTI2016

Solvation structure of the halides from x-ray absorption spectroscopy

Three-dimensional models for the aqueous solvation structures of chloride, bromide, and iodide are reported. K-edge extended X-ray absorption fine structure (EXAFS) and Minuit X-ray absorption near edge (MXAN) analyses found well-defined single shell solvation spheres for bromide and iodide. However, dissolved chloride proved structurally distinct, with two solvation shells needed to explain its strikingly different X-ray absorption near edge structure (XANES) spectrum. Final solvation models were as follows: iodide, 8 water molecules at 3.60 ± 0.13 Å and bromide, 8 water molecules at 3.40 ± 0.14 Å, while chloride solvation included 7 water molecules at 3.15 ± 0.10 Å, and a second shell of 7 water molecules at 4.14 ± 0.30 Å. Each of the three derived solvation shells is approximately uniformly disposed about the halides, with no global asymmetry. Time-dependent density functional theory calculations simulating the chloride XANES spectra following from alternative solvation spheres revealed surprising sensitivity of the electronic state to 6-, 7-, or 8-coordination, implying a strongly bounded phase space for the correct structure during an MXAN fit. MXAN analysis further showed that the asymmetric solvation predicted from molecular dynamics simulations using halide polarization can play no significant part in bulk solvation. Classical molecular dynamics used to explore chloride solvation found a 7-water solvation shell at 3.12 (−0.04/+0.3) Å, supporting the experimental result. These experiments provide the first fully three-dimensional structures presenting to atomic resolution the aqueous solvation spheres of the larger halide ions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

Correlations and Cascades in Magnetized Turbulence

Many terrestrial and astrophysical plasmas encompass very large dynamical ranges in space and time, which are not accessible by direct numerical simulations. Thus, idealized subvolumes are often used to study small-scale effects including the dynamics of magnetized turbulence. A significant aspect of magnetized turbulence is the transfer of energy from large to small scales, in part through the operation of a turbulent cascade. In this work, we present a new shell-to-shell energy transfer analysis framework for understanding energy transfer within magnetized turbulence and in particular, through the cascade. We demonstrate the viability of this framework through application to a series of isothermal subsonic and supersonic simulations of compressible magnetized turbulence and utilize results from this analysis to establish a non-linear benchmark for compressible magnetized turbulence in the subsonic regime. We further study how the autocorrelation time of the driving and its normalization systematically change properties of compressible magnetized turbulence. For example, we find that 6-in-time forcing with a constant energy injection leads to a steeper slope in kinetic energy spectrum and less efficient small-scale dynamo action. We examine how these results can impact a range of diagnostics relevant for a range of terrestrial and astrophysical applications.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2017

Investigating the Origins of Two Extreme Solar Particle Events: Proton Source Profile and Associated Electromagnetic Emissions

We analyze the high-energy particle emission from the Sun in two extreme solar particle events in which protons are accelerated to relativistic energies and can cause a significant signal even in the ground-based particle detectors. Analysis of a relativistic proton event is based on modeling of the particle transport and interaction, from a near-Sun source through the solar wind and the Earth’s magnetosphere and atmosphere to a detector on the ground. This allows us to deduce the time profile of the proton source at the Sun and compare it with observed electromagnetic emissions. The 1998 May 2 event is associated with a flare and a coronal mass ejection (CME), which were well observed by the Nançay Radioheliograph, thus the images of the radio sources are available. For the 2003 November 2 event, the low corona images of the CME liftoff obtained at the Mauna Loa Solar Observatory are available. Those complementary data sets are analyzed jointly with the broadband dynamic radio spectra, EUV images, and other data available for both events. We find a common scenario for both eruptions, including the flare’s dual impulsive phase, the CME-launch-associated decimetric-continuum burst, and the late, low-frequency type III radio bursts at the time of the relativistic proton injection into the interplanetary medium. The analysis supports the idea that the two considered events start with emission of relativistic protons previously accelerated during the flare and CME launch, then trapped in large-scale magnetic loops and later released by the expanding CME.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Elucidating the Onset of Plasticity in Sliding Contacts Using Differential Computational Orientation Tomography

Abstract Depending on the mechanical and thermal energy introduced to a dry sliding interface, the near-surface regions of the mated bodies may undergo plastic deformation. In this work, we use large-scale molecular dynamics simulations to generate “differential computational orientation tomographs” (dCOT) and thus highlight changes to the microstructure near tribological FCC alloy surfaces, allowing us to detect subtle differences in lattice orientation and small distances in grain boundary migration. The analysis approach compares computationally generated orientation tomographs with their undeformed counterparts via a simple image analysis filter. We use our visualization method to discuss the acting microstructural mechanisms in a load- and time-resolved fashion, focusing on sliding conditions that lead to twinning, partial lattice rotation, and grain boundary-dominated processes. Extracting and laterally averaging the color saturation value of the generated tomographs allows us to produce quantitative time- and depth-resolved maps that give a good overview of the progress and severity of near-surface deformation. Corresponding maps of the lateral standard deviation in the color saturation show evidence of homogenization processes occurring in the tribologically loaded microstructure, frequently leading to the formation of a well-defined separation between deformed and undeformed regions. When integrated into a computational materials engineering framework, our approach could help optimize material design for tribological and other deformation problems. Graphic Abstract .

36 MATERIALS SCIENCE↗
DOE OSTI2018

Freshwater carbon and nutrient cycles revealed through reconstructed population genomes

Although microbes mediate much of the biogeochemical cycling in freshwater, the categories of carbon and nutrients currently used in models of freshwater biogeochemical cycling are too broad to be relevant on a microbial scale. One way to improve these models is to incorporate microbial data. Here, we analyze both genes and genomes from three metagenomic time series and propose specific roles for microbial taxa in freshwater biogeochemical cycles. Our metagenomic time series span multiple years and originate from a eutrophic lake (Lake Mendota) and a humic lake (Trout Bog Lake) with contrasting water chemistry. Our analysis highlights the role of polyamines in the nitrogen cycle, the diversity of diazotrophs between lake types, the balance of assimilatory vs. dissimilatory sulfate reduction in freshwater, the various associations between types of phototrophy and carbon fixation, and the density and diversity of glycoside hydrolases in freshwater microbes. We also investigated aspects of central metabolism such as hydrogen metabolism, oxidative phosphorylation, methylotrophy, and sugar degradation. Finally, by analyzing the dynamics over time in nitrogen fixation genes and Cyanobacteria genomes, we show that the potential for nitrogen fixation is linked to specific populations in Lake Mendota. This work represents an important step towards incorporating microbial data into ecosystem models and provides a better understanding of how microbes may participate in freshwater biogeochemical cycling.

58 GEOSCIENCES↗
DOE OSTI2025

Model-based Hierarchical Reinforcement Learning for Improved Physical Security Design: A Prototype

Prior work in FY24 developed an adversarial AI agent aid in path analysis of physical protection systems. This agent, trained using a model-based reinforcement learning algorithm, was able to successfully learn the most vulnerable path in facilities. It was able to extend the current state of practice for physical protection design by exhibiting dynamic behavior based on current environmental conditions. Whereas PathTrace largely performs a static, graph-based analysis, the AI agent was able to make decisions based on relative position in the facility, current conditions (was the adversarial agnet discovered?), and proximity to secondary targets. The agent demonstrated some novel capabilities, but had limitations that need to be resolved before it can be used for production purposes. For example, the adversarial agent generalizes poorly and takes a relatively long time to train. Nonetheless, there is still considerable promise for developing the adversarial agent further in order to explore even richer, more dynamic behaviors (e.g., adversary motivations, environmental debris, and more). This work considers a complementary idea; development of a planning agent. The planning agent is envisioned as an auto-complete-like tool that can help accelerate security system design by human experts. The agent would respect existing barriers and sensors placed by a human expert while offering cost-effective suggestions (i.e., implicitly balancing effectiveness with cost) to improve the design. The goal is for this agent to be part of an expert’s toolbox, not to totally upend the current state-of-practice, or to displace human experts. The ultimate goal would be concurrent training of both the adversarial and planning agent together, to learn entirely through self-play. This would represent an entirely new way of performing system deign. We selected a hierarchical, model-based reinforcement learning algorithm to serve as the planning agent. This is an extension of concepts used in the prior FY24 adversarial agent work. There, we had a single agent acting an environment. Here, we have two different sub-agents (policies), working together, to form a complete agent. There is a manager policy, which can select abstract goals on slower time scales, and a worker, which performs primitive actions to reach goals selected by the manager. It is worth noting that this class of algorithm is challenging to work with. From our understanding, our work is one of the first successful uses of model-based reinforcement learning (MBRL) in nuclear energy1 , and likely the first hierarchical model-based reinforcement learning application in nuclear energy. Further, this work is one of the first known attempts to apply AI to perform a design tasks in nuclear energy. Consequently, there were significant implementation challenges and the bulk of the work was focused on successful implementation and algorithm design. The results presented here are very low technology readiness level as a consequence of the lack of related literature, but still represent a significant step forward in the pursuit of applied AI for design.

42 ENGINEERING↗
DOE OSTI2016

Statistical Study of Primary Knock-on Atoms under Neutron Irradiation in RMC Code

Materials in high flux neutron condition will suffer from an evolution of damage which ultimately restricts the lifetime of the fuel clad and reactor pressure vessel. Atoms in irradiated material transform to primary knock-on atoms (PKAs) by absorbing the kinetic energy transferred from neutrons, and the energy released from nuclear reactions. The secondary collision cascades which are induced by PKAs create point defects within the material, with residual vacancies and interstitials eventually causing swelling and embrittlement that degrades mechanical behavior. For a long time, Displacements per Atom (DPA) index has been identified as a measure of radiation damage in material. Nowadays, several advanced methods, such as Molecular Dynamics (MD) and Kinetic Monte Carlo (KMC) simulations, have been developed for more accurately simulating the evolution of the damage. However, all of these techniques need more comprehensive information of PKA, such as the type, energy, direction and spatial distribution. The limitations of DPA emerge and a method should be provided to simulate the generative process of PKAs. Recently, a deterministic analysis code SPECTRA-PKA has been developed by Gilbert to calculate the energy spectra of almost all types PKAs by solving the group-to-group cross-section matrices equation which includes neutron scattering, light charged particles, and recoils of the residual nuclei. But this deterministic analysis code could not give the direction, spatial and time distribution of PKAs. Based on the Geant4 program, Cui Zhenguo has simulated the irradiation by neutrons with 1 MeV energy in zirconium, while only the two adjacent elastic collisions between injected neutron and target atoms are taken into consideration. In this paper, Monte Carlo method to calculate PKAs information during neutron transport in RMC code is introduced. RMC is a continuous-energy Reactor Monte Carlo neutron and photon transport code being developed by Department of Engineering Physics at Tsinghua University, Beijing. PKAs in zirconium are calculated in fixed neutron source mode. Statistical information of PKAs in PWR fuel cell and SFR fuel cell is shown and compared. The results show that Monte Carlo method can provide more comprehensive information of PKAs. (authors)

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2015

Preserving correlations between trajectories for efficient path sampling

Importance sampling of trajectories has proved a uniquely successful strategy for exploring rare dynamical behaviors of complex systems in an unbiased way. Carrying out this sampling, however, requires an ability to propose changes to dynamical pathways that are substantial, yet sufficiently modest to obtain reasonable acceptance rates. Satisfying this requirement becomes very challenging in the case of long trajectories, due to the characteristic divergences of chaotic dynamics. Here, we examine schemes for addressing this problem, which engineer correlation between a trial trajectory and its reference path, for instance using artificial forces. Our analysis is facilitated by a modern perspective on Markov chain Monte Carlo sampling, inspired by non-equilibrium statistical mechanics, which clarifies the types of sampling strategies that can scale to long trajectories. Viewed in this light, the most promising such strategy guides a trial trajectory by manipulating the sequence of random numbers that advance its stochastic time evolution, as done in a handful of existing methods. In cases where this “noise guidance” synchronizes trajectories effectively, as the Glauber dynamics of a two-dimensional Ising model, we show that efficient path sampling can be achieved for even very long trajectories.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2018

Instanton liquid properties from lattice QCD

Here, we examined the instanton contribution to the QCD configurations generated from lattice QCD for N F = 0, N F = 2 + 1 and N F = 2 + 1 + 1 dynamical quark flavors from two different and complementary approaches. First via the use of Gradient flow, we computed instanton liquid properties using an algorithm to localize instantons in the gauge field configurations and studied their evolution with flow time. Then, the analysis of the running at low momenta of gluon Green's functions serves as an independent confirmation of the instanton density which can also be derived without the use of the Gradient flow.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2016

Nonintrusive Uncertainty Quantification of Computational Fluid Dynamics Simulations of a Bench-Scale Fluidized-Bed Gasifier

Uncertainty quantification (UQ) analysis is increasingly becoming one of the major requirements of simulation-based engineering to assess the confidence in the results and make better-informed decisions based on the insight derived from the simulations. In an earlier study, Bayesian UQ analysis was applied to existing bench-scale fluidized-bed gasifier experiment results. In the current study, a series of simulations were carried over with the open-source computational fluid dynamics software MFiX to reproduce the experimental conditions, where three operating factors, i.e., coal flow rate, coal particle diameter, and steam-to-oxygen ratio, were systematically varied to understand their effect on the syngas composition. Bayesian UQ analysis was this time performed on the numerical results for comparison purposes. This is part of ongoing research efforts to explore the applicability of advanced UQ methods and processes such as Bayesian methods for large-scale complex multiphase flow simulations. As part of Bayesian UQ analysis, a global sensitivity analysis was performed based on the simulation results, which shows that the predicted syngas composition is strongly affected not only by the steam-to-oxygen ratio (which was observed in experiments as well) but also by variation in the coal flow rate and particle diameter (which was not observed in experiments). The carbon monoxide mole fraction is underpredicted at lower steam-to-oxygen ratios and overpredicted at higher steam-to-oxygen ratios. The opposite trend is observed for the carbon dioxide mole fraction. These discrepancies are attributed to either excessive segregation of the phases that leads to the fuel-rich or -lean regions or alternatively the selection of reaction models, where different reaction models and kinetics can lead to different syngas compositions throughout the gasifier.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2025

Exploring Domain-Wall Pinning in Ferroelectrics via Automated High-Throughput Atomic Force Microscopy

Domain-wall dynamics in ferroelectric materials are strongly position-dependent, since each polar interface is locked into a unique local microstructure. This necessitates spatially resolved studies of wall pinning using scanning-probe microscopy techniques. The pinning centers and pre-existing domain walls are usually sparse within the image plane, precluding the use of dense hyperspectral imaging modes and requiring time-consuming human experimentation. Here, a large-area epitaxial PbTiO 3 film on cubic KTaO 3 was investigated to quantify the electric-field-driven dynamics of the polar–strain domain structures using ML-controlled automated piezoresponse force microscopy. Analysis of 1500 switching events reveals that domain-wall displacement depends not only on field parameters but also on the local ferroelectric–ferroelastic configuration. For example, twin boundaries in polydomains regions, like a 1 – /c+ ∥ a 2 – /c – , stay pinned up to a certain level of bias magnitude and change only marginally as the bias increases from 20 to 30 V, whereas single-variant boundaries, like the a 2 + /c + ∥ a 2 – /c – stack, are already activated at 20 V. These statistics on the possible ferroelectric and ferroelastic wall orientations, together with the automated high-throughput AFM workflow, can be distilled into a predictive map that links domain configurations to pulse parameters. Here, this microstructure-specific rule set forms the foundation for the design of ferroelectric memories.

automated scanning probe microscopy↗
DOE OSTI2015

Field propagation-induced directionality of carrier-envelope phase-controlled photoemission from nanospheres

Near-fields of non-resonantly laser-excited nanostructures enable strong localization of ultrashort light fields and have opened novel routes to fundamentally modify and control electronic strong-field processes. Harnessing spatiotemporally tunable near-fields for the steering of sub-cycle electron dynamics may enable ultrafast optoelectronic devices and unprecedented control in the generation of attosecond electron and photon pulses. Here we utilize unsupported sub-wavelength dielectric nanospheres to generate near-fields with adjustable structure and study the resulting strong-field dynamics via photoelectron imaging. We demonstrate field propagation-induced tunability of the emission direction of fast recollision electrons up to a regime, where nonlinear charge interaction effects become dominant in the acceleration process. In conclusion, our analysis supports that the timing of the recollision process remains controllable with attosecond resolution by the carrier-envelope phase, indicating the possibility to expand near-field-mediated control far into the realm of high-field phenomena.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2017

Influence of low concentrations of scatterers and signal detection time on the results of their measurements using dynamic light scattering

The influence of limited detection time on the form of the autocorrelation function (ACF) has been analysed for measurements in low-concentration suspensions by dynamic light scattering with allowance for the spatial distribution of the laser beam intensity. The general view of the ACF of the scattered light intensity is obtained for a Gaussian beam and a finite measurement time. The results of the theoretical analysis are compared with the experimental data and the results obtained by computer simulation of the scattering from an ensemble of particles involved in Brownian motion in a Gaussian beam. It is shown that, in the case of low suspension concentrations, the ACF distortions related to finite detection time lead to underestimation of the particle sizes and occurrence of an artefact peak in the distribution of the scattered light intensity over scatterer sizes. An empirical dependence of the measured size of particles on their number in the scattering volume is found. (light scattering)

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2015

Dynamical behavior in mimetic F(R) gravity

We investigate the cosmological behavior of mimetic F(R) gravity. This scenario is the F(R) extension of usual mimetic gravity classes, which are based on re-parametrizations of the metric using new, but not propagating, degrees of freedom, that can lead to a wider family of solutions. Performing a detailed dynamical analysis for exponential, power-law, and arbitrary F(R) forms, we extracted the corresponding critical points. Interestingly enough, we found that although the new features of mimetic F(R) gravity can affect the universe evolution at early and intermediate times, at late times they will not have any effect, and the universe will result at stable states that coincide with those of usual F(R) gravity. However, this feature holds for the late-time background evolution only. On the contrary, the behavior of the perturbations is expected to be different since the new term contributes to the perturbations even if it does not contribute at the background level.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

From inflation to recent cosmic acceleration: the fermionic Elko field driving the evolution of the universe

In this paper we construct the complete evolution of the universe driven by the mass dimension one dark spinor called Elko, starting with inflation, passing by the matter dominated era and finishing with the recent accelerated expansion. The dynamic of the fermionic Elko field with a symmetry breaking type potential can reproduce all phases of the universe in a natural and elegant way. The dynamical equations in general case and slow roll conditions in the limit H || m {sub pl} are also presented for the Elko system. Numerical analysis for the number of e-foldings during inflation, energy density after inflation and for present time and also the actual size of the universe are in good agreement with the standard model of cosmology. An interpretation of the inflationary phase as a result of Pauli exclusion principle is also possible if the Elko field is treated as an average value of its quantum analogue.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Efficacy of the Method of Four Coefficients to Determine Charge-Carrier Scattering

The investigation of the electronic properties of semiconductors from transport measurements (i.e., resistivity, Hall, and Seebeck coefficient measurements) is challenging due to the averaging of charge-carrier dynamics inherent in such measurements. Here, we investigate the incorporation of a fourth measurement of electronic transport, the Nernst coefficient, into the analysis, termed the method of four coefficients. This approach yields the Fermi level, effective mass, scattering exponent, and relaxation time prefactor. We begin with a review of the underlying mathematics and investigate the mapping between the four-dimensional material property and transport coefficient spaces. We then investigate how the traditional single-parabolic band method yields a single, potentially incorrect point on the solution subspace. This uncertainty can be resolved through Nernst coefficient measurements and we map the span of the ensuing subspace. We conclude with an investigation of how sensitive the analysis of transport coefficients is to experimental error for different sample types.

charge carriers↗