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At least 721 records · Page 40

In situ irradiation of spent nuclear fuels

To improve the economics of commercial nuclear reactors, nuclear vendors and utilities are seeking approval for increased burnup usage of the existing nuclear fleet. This is especially critical for meeting the clean energy initiative by the United States Government, Department of Energy (DOE). However, one of the key challenges the nuclear industry faces in this regard is that the regions exposed to high burnup and low temperatures exhibit a fine-grained microstructure with large bubbles known as high-burnup structure (HBS) [1]. The formation of HBS has been correlated to the diminished performance of the reactor, as well as fuel fragmentation and pulverization during transient and accidental conditions [2]. Therefore, it is paramount to understand the mechanisms for HBS formation along with its impact on the properties and performance of nuclear fuels. While existing programs, such as Nuclear Energy Advanced Modeling and Simulation (NEAMS) and Advanced Fuel Campaign (AFC) are focusing on evaluating the performance impact of HBS, the physical mechanisms contributing to HBS formation are still not fully understood. In addition, having predictive capabilities and sound understanding of the microstructural evolution of nuclear fuel is essential for accelerated development, qualification, and deployment of new nuclear materials and novel reactor designs for advanced nuclear reactors. There is a lack of consensus among researchers regarding the mechanisms leading to such restructuring observed in HBS. Grain subdivision due to polygonization versus recrystallization, continuous versus discrete recrystallization occurring in tandem or conjunction, etc., have been proposed and debated. In general, it is hypothesized that defect accumulation and dislocation interaction within the grains cause the realignment of dislocations into grain boundaries, leading to the new subgrain formation, which over time transforms into new grains. However, due to the lack of transient data, the importance of fission rate, irradiation, thermal, and stress history of the fuel on the restructuring could not be assessed. In situ microstructural evolution under various irradiation conditions is desired to bridge this gap. Alternatively, phase-field-based models have been developed to capture HBS formation via discrete recrystallization utilizing the classical nucleation approach [3–5]. However, in these models, the grain nucleation criteria are often defined based on empirical relations for burnup and fission gas density leading to dislocation density change. A mechanistic approach to capture the dislocation interaction with the microstructural features leading to grain subdivision is lacking.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Modeled Results of Four Residential Energy Efficiency Measure Packages for Deriving Advanced Building Construction Research Targets

The Advanced Building Construction (ABC) Initiative from the U.S. Department of Energy Building Technologies Office is working to accelerate industrialized construction innovations for decarbonizing buildings. To inform performance and cost targets for research under the ABC Initiative, this analysis used the ResStock™ tool to evaluate the energy savings, utility bill impacts, and carbon emissions impacts of four simulated upgrade packages with specific target performance levels on a large sample of residential dwelling units (approximately 550,000) representative of the U.S. housing stock.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Convergence study of wakefield simulations with GdfidL and ECHO3D

The interaction of charged particle beams with vacuum chamber components gives rise to electromagnetic wakefields, whose frequency-domain representation is known as beam coupling impedance. Geometric impedance arising from discontinuities and transitions in the vacuum chamber is the focus of this study. Minimizing this impedance is essential to mitigate adverse collective effects in modern storage rings operating with high-intensity particle beams. Accurate and reliable impedance simulations is a key factor of the vacuum chamber design. This paper presents the results of a convergence study of two widely used electromagnetic solvers, GdfidL and ECHO3D, applied to key vacuum-chamber components of the National Synchrotron Light Source II (NSLS-II) storage ring. Detailed comparisons are performed for several geometries, including flange absorbers, RF bellows, button-type beam position monitors, and an in-vacuum undulator (IVU). The results show notable differences in convergence and computational efficiency between the two codes. While GdfidL provides highly resolved results and serves as a common benchmark tool, ECHO3D yields consistent results with coarser meshes, significantly reducing simulation time and memory demands. Simulations with a full-geometry IVU model demonstrate that simplified taper-transition models can miss important impedance contributions. In conclusion, these findings provide practical guidelines for efficient and accurate impedance modeling to optimize design of vacuum chamber components for accelerators.

36 MATERIALS SCIENCE↗

Design of Controller Hardware-In-the-Loop Model of Microgrid with Modular Building Blocks and Automated Design Script

The scalability of controller hardware-in-the-loop (CHIL) simulation is critical for validating control coordination and energy management in microgrids with distributed energy resources, especially as these modern systems become more complex and decentralized. This paper presents a CHIL modeling methodology that combines modular building blocks with an automated design script to streamline the development of high-fidelity microgrid models. Standardized subsystem templates for resources, converters, and buses are integrated with a Python-based script that compiles structured JSON configuration files into simulation-ready initialization code. The proposed approach reduces development time, improves model consistency, and enhances simulation fidelity. The methodology is validated on a Typhoon HIL604 platform and is broadly applicable to real-time simulation of complex, networked microgrid systems. This framework establishes a foundation for automated, scalable CHIL validation and accelerates the design of next-generation distributed energy systems.

Kim, Namwon [ORNL] (ORCID:0000000200438489)↗

Active Learning Framework

Machine learning (ML) of interatomic potentials show great promise to accelerate scientific simulation, e.g., by emulating expensive computations at a high accuracy but much reduced computational cost. Training datasets are calculated from computationally expensive ab initio quantum mechanics methods, density functional theory (DFT). Trained on this data, an ML model can be very successful in predicting energy and forces for new atomic configurations. A critical factor is the quality and diversity of the training dataset. Thus, a highly automated approach to dataset construction based on active learning framework is designed suitable for material physics. The active learning scheme begins with fully randomized atomic configurations. Then, many Molecular Dynamics (MD) trajectories are simulated using current ML potentials, where each MD trajectory is initialized to a random disordered configuration. The temperature is varied in order to diversify the sampled configuration during these simulations. The variance of predictions for eight neural networks within an ensemble is analyzed to determine whether the model is operating as expected. This helps in determining whether collecting more data would be helpful to the model by checking the ensemble variance is greater than the threshold. In this case, the MD trajectory is terminated and the final atomic configuration is placed on a queue (SQL database) for DFT calculations and added to training dataset. Periodically, ML model is retrained to the updated training model. This Active Learning loop is iterated until the cost of MD simulations becomes prohibitively expensive. The MD simulations will hopefully be sufficiently robust to support nucleation after many active learning iterations. In this sense, active learning scheme must automatically discover the important low energy and nonequilibrium physics.

Nebgen, Benjamin↗

Intermittency and Dissipative Structures Arising from Relativistic Magnetized Turbulence

Abstract Kinetic simulations of relativistic turbulence have significantly advanced our understanding of turbulent particle acceleration. Recent progress has highlighted the need for an updated acceleration theory that can account for particle acceleration within the plasma’s coherent structures. Here, we investigate how intermittency modeling connects statistical fluctuations in turbulence to regions of high-energy dissipation. This connection is established by employing a generalized She–Leveque model to characterize the exponents ζ p for the structure functions S p ∝ l ζ p . The fitting of the scaling exponents provides us with a measure of the codimension of the dissipative structures, for which we subsequently determine the filling fraction. We perform our analysis for a range of magnetizations σ and relative fluctuation amplitudes δ B 0 / B 0 . We find that increasing values of σ and δ B 0 / B 0 allow the turbulent cascade to break sheetlike structures into smaller regions of dissipation that resemble chains of flux ropes. However, as their dissipation measure increases, the dissipative regions become less volume filling. With this work, we aim to inform future turbulent acceleration theories that incorporate particle energization from interactions with coherent structures within relativistic turbulence.

Astronomy & Astrophysics↗

Double-power-law Feature of Energetic Particles Accelerated at Coronal Shocks

Recent observations have shown that in many large solar energetic particle (SEP) events the event-integrated differential spectra resemble double power laws. We perform numerical modeling of particle acceleration at coronal shocks propagating through a streamer-like magnetic field by solving the Parker transport equation, including protons and heavier ions. We find that for all ion species the energy spectra integrated over the simulation domain can be described by a double power law, and the break energy depends on the ion charge-to-mass ratio as E B ~ (Q/A) α , with α varying from 0.16 to 1.2 by considering different turbulence spectral indices. We suggest that the double-power-law distribution may emerge as a result of the superposition of energetic particles from different source regions where the acceleration rates differ significantly due to particle diffusion. The diffusion and mixing of energetic particles could also provide an explanation for the increase of Fe/O at high energies as observed in some SEP events. Although further mixing processes may occur, our simulations indicate that either a power-law break or rollover can occur near the Sun and predict that the spectral forms vary significantly along the shock front, which may be examined by upcoming near-Sun SEP measurements from the Parker Solar Probe and Solar Orbiter.

79 ASTRONOMY AND ASTROPHYSICS↗

Drying of tundra landscapes will limit subsidence-induced acceleration of permafrost thaw: Modeling Archive

This Modeling Archive is in support of a NGEE Arctic publication in review "Drying of tundra landscapes will limit subsidence-induced acceleration of permafrost thaw". The study used a cryohydrology model to assess the potential risk of abrupt permafrost thaw triggered by melting ground ice, a key open question associated with permafrost response to a warming Arctic. The spatially resolved simulations are for a small catchment 465 ice-wedge polygons in polygonal tundra near Utqiagvik, Alaska in the high-emissions RCP8.5 climate scenario. The simulations are compared to runoff, evapotranspiration and subsidence in the current climate and agree well. The study used the ATS code configured as an intermediate-scale cryohydrology model (Advanced Terrestrial Simulator, Version v2). The archive includes input files for spinup (1985 to 2005) and projections (2006 to 2100 - the manuscript reports 2006 to 2098). Three of the projections include the effects of subsidence and microtopography change with different depth profiles of ice content corresponding to the median, 20th percentile and 80th percentile. The fourth projection has subsidence turnoff and uses the reference case (median) ice content. Spatially averaged or aggregated output variables are included for the projections. Selected checkpoint files for the projections and postprocessing scripts are also included. Files included are *.xml; *.h5; *.exo; *.py; *.sh, *. nb, mesh files, and one file in the original Excel format plus *.csv and *.pdf to conserve formatting contained in the original file. The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗

DNS of a Simplified Gas Turbine Premixer: Auto-Ignition and Flame Stabilization

With the increasing need for fuel-flexibility, an understanding of auto-ignition inside gas turbine premixers is crucial. Direct numerical simulation (DNS) is a great tool to reveal the fine grain details of physics inside the premixer and guide the choice of the models to use for less expensive simulations. We present numerical simulations of a simplified and downscaled premixer, with multiple air jets in rich fuel crossflow. The simulations show intense fuel-air mixing and flame-turbulence interaction. We examine flow acceleration by the incoming jets, and the combustion within the device. We observe low-temperature and high-temperature combustion signatures, and compute the flame index to quantify local stabilization modes.

combustion↗

Freeze range of a condensing gas propagating in a liquid helium-cooled tube

Understanding air propagation and condensation following a catastrophic vacuum break in particle accelerator beamlines cooled by liquid helium is crucial for maintaining the operational safety of these facilities. Previous experimental investigations on nitrogen gas propagation in both normal liquid helium (He I) and superfluid helium (He II) cooled copper tubes unveiled a nearly exponential deceleration of the gas propagation. A comprehensive theoretical model incorporating gas dynamics, heat transfer, and condensation mechanisms has been developed, which effectively reproduces various key experimental observations. An intriguing phenomenon uncovered in our model simulation is that the gas propagation appears to nearly stop beyond a certain distance from the location where condensation starts. We refer to this distance as the freeze range. In this paper, we present our systematic study of the freeze range at various inlet mass fluxes and tube diameters. We show that the results can be well described by a simple correlation. The underlying physical mechanism that supports this useful correlation is explained. Knowing the freeze range may allow accelerator engineers to develop protocols for controlling frost-layer contamination in the beamline tubes, which is of great practical importance.

43 PARTICLE ACCELERATORS↗

Experimental characterization of discharge plasma dynamics in a square capillary for prospective applications in laser wakefield acceleration

Research on plasma generated by electrical discharge in gas-filled capillaries plays an important role in advancing laser wakefield accelerators. We present a comprehensive study of the temporal and spatial distribution of plasma density within a short, 1 cm long, square-shaped capillary filled with hydrogen gas. Two transverse capillary sizes, 500 μm and 300 μm, were investigated achieving peak plasma densities of 0.9 × 10 18 cm −3 and 2.5 × 10 18 cm −3 , respectively, at the capillary center. In addition, we explore how these distributions depend on discharge parameters, specifically discharge current and gas flow through the capillary. Plasma density was determined by analyzing the Stark broadening of the hydrogen Balmer-alpha line. The results obtained were compared with the theoretical models and simulations. The comparison between the model predictions and the experimental data at the transient ionization stage of the discharge reveals a discrepancy of a factor of ∼1.3–2.1, depending on the capillary size, which is thoroughly discussed.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

LDRD for a high-current polarized-beam photogun

The electron accelerator driving the Ce+BAF conversion target requires a spin-polarized photogun capable of delivering a CW beam current of at least 1 mA. As the high beam current limits the useful operating time of the gun between photocathode reactivations due to ion back-bombardment, it is critical to increase the charge lifetime. A Jefferson Lab LDRD project aims to calibrate the simulation models needed to predict photocathode lifetime as a function of electrostatic optics and drive laser parameters in order to design a gun providing at least 1000 C charge lifetime. A prototype gun demonstrating the validity of the scaling predictions will be built and tested at the Gun Test Stand. I will describe the background and progress of this project and give an outlook on the expected performance.

Bruker, Max [Thomas Jefferson National Accelerator↗

Enhancing the Quality and Reliability of Machine Learning Interatomic Potentials through Better Reporting Practices

Recent developments in machine learning interatomic potentials (MLIPs) have empowered even nonexperts in machine learning to train MLIPs for accelerating materials simulations. However, reproducibility and independent evaluation of presented MLIP results is hindered by a lack of clear standards in current literature. In this Perspective, we aim to provide guidance on best practices for documenting MLIP use while walking the reader through the development and deployment of MLIPs including hardware and software requirements, generating training data, training models, validating predictions, and MLIP inference. We also suggest useful plotting practices and analyses to validate and boost confidence in the deployed models. Finally, we provide a step-by-step checklist for practitioners to use directly before publication to standardize the information to be reported. Altogether, we hope that our work will encourage the reliable and reproducible use of these MLIPs, which will accelerate their ability to make a positive impact in various disciplines including materials science, chemistry, and biology, among others.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Modelling Beam Loss Within the LANSCE Proton Storage Ring

Several upgrades are being considered for the proton storage ring (PSR) at the Los Alamos Neutron Science Center (LANSCE) to reduce beam loss and thereby reduce the cooldown period of the PSR following a beam run. First, we have considered an increased beam pipe diameter would reduce beam loss due to beam scraping caused by misalignments and tuning errors. However, this would require increased pole-to-pole gap height within the dipoles and quadrupoles, which would change their effective length and alter their fringe fields. The effect of different magnet gaps on the beam optical parameters and on beam loss was studied using the simulation codes MAD-X and PyORBIT. Second, we are developing a detailed particle tracking model within the framework of the simulation package General Particle Tracer (GPT) for the PSR H - stripping system. This model will be used to study the effect of the stripper foil parameters (position, composition, areal density, depth, etc.) on first-turn losses, where most of the observed beam loss and emittance growth occurs due to foil scattering, foil stripping, and Lorentz stripping. The model implements C++ custom elements created to model foil scattering, foil stripping, and Lorentz stripping, as these are not built-in features of GPT. The preliminary results of the MAD-X and PyORBIT simulations, as well as the GPT simulation model, is described in this tech note.

43 PARTICLE ACCELERATORS↗

MLSPICE: Machine Learning based SPICE Modeling Platform for Power Magnetics

Electrical power converters are critical to a wide range of applications ranging from renewable integration to transportation electrification, and can be a key factor determining the size, weight, and efficiency of energy conversion systems. Magnetic components are typically the largest and least efficient components in power electronics. While there have been major strides in the modeling and analysis of power semiconductor devices and circuit simulations, the necessary advances in the design of power magnetics have lagged. In this project, we have transformed the modeling and design of power magnetics with machine learning enabled methods and catalyze simultaneous disruptive improvements for ML-based power electronics design tools. A fully automated open-source machine learning based magnetics modeling platform – the MagNet project - with innovations in full stack have been developed to greatly accelerate the design process and provide new insights to magnetic material and geometry design. The ARPA-E funded MagNet platform contains three major building blocks: 1) a ML-Integrated Data Acquisition System (MIDAS): a highly automated data acquisition testbed which is capable of measuring a large number of magnetic cores with a wide range of electrical circuit excitations; 2) a ML-integrated Core Loss Model (MICLM): a machine-learning trained modeling method for modeling the core loss and saturation effects of magnetic materials for arbitrary excitation waveforms; 3) ML-guided Magnetics SPICE Simulation Tool (PMSPICE): a fully integrated CAD tool which can simulate the magnetics in SPICE. It can help the designers to quickly model the linear and non-linear characteristics of magnetic components and evaluate their behavior in SPICE simulations. The developed MagNet system has fully demonstrated the proposed performance target and has been open sourced to the entire power electronics community to advance the modeling and design of power magnetics from many different angles.

36 MATERIALS SCIENCE↗

Fast electron transport dynamics and energy deposition in magnetized, imploded cylindrical plasma

Inertial confinement fusion approaches involve the creation of high-energy-density states through compression. High gain scenarios may be enabled by the beneficial heating from fast electrons produced with an intense laser and by energy containment with a high-strength magnetic field. Here, we report experimental measurements from a configuration integrating a magnetized, imploded cylindrical plasma and intense laser-driven electrons as well as multi-stage simulations that show fast electrons transport pathways at different times during the implosion and quantify their energy deposition contribution. The experiment consisted of a CH foam cylinder, inside an external coaxial magnetic field of 5 T, that was imploded using 36 OMEGA laser beams. Two-dimensional (2D) hydrodynamic modelling predicts the CH density reaches 9.0 g cm − 3 , the temperature reaches 920 eV and the external B-field is amplified at maximum compression to 580 T. At pre-determined times during the compression, the intense OMEGA EP laser irradiated one end of the cylinder to accelerate relativistic electrons into the dense imploded plasma providing additional heating. The relativistic electron beam generation was simulated using a 2D particle-in-cell (PIC) code. Finally, three-dimensional hybrid-PIC simulations calculated the electron propagation and energy deposition inside the target and revealed the roles the compressed and self-generated B-fields play in transport. During a time window before the maximum compression time, the self-generated B-field on the compression front confines the injected electrons inside the target, increasing the temperature through Joule heating. For a stronger B-field seed of 20 T, the electrons are predicted to be guided into the compressed target and provide additional collisional heating. This article is part of a discussion meeting issue ‘Prospects for high gain inertial fusion energy (part 2)’.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Fast and scalable quantum Monte Carlo simulations of electron-phonon models

We introduce methodologies for highly scalable quantum Monte Carlo simulations of electron-phonon models, and report benchmark results for the Holstein model on the square lattice. The determinant quantum Monte Carlo (DQMC) method is a widely used tool for simulating simple electron-phonon models at finite temperatures, but incurs a computational cost that scales cubically with system size. Alternatively, near-linear scaling with system size can be achieved with the hybrid Monte Carlo (HMC) method and an integral representation of the Fermion determinant. Here, we introduce a collection of methodologies that make such simulations even faster. To combat "stiffness" arising from the bosonic action, we review how Fourier acceleration can be combined with time-step splitting. To overcome phonon sampling barriers associated with strongly-bound bipolaron formation, we design global Monte Carlo updates that approximately respect particle-hole symmetry. To accelerate the iterative linear solver, we introduce a preconditioner that becomes exact in the adiabatic limit of infinite atomic mass. Finally, we demonstrate how stochastic measurements can be accelerated using fast Fourier transforms. Here, these methods are all complementary and, combined, may produce multiple orders of magnitude speedup, depending on model details.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗