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At least 1,135 records · Page 63

Determination of Experimental Fuel Rod Parameters using 3D Modelling of PCMI with MPS Defect

An in-reactor experiment is being designed in order to validate the pellet-cladding mechanical interaction (PCMI) behavior of the BISON fuel performance code. The experimental parameters for the test rod being placed in the Halden Research Reactor are being determined using BISON simulations. The 3D model includes a missing pellet surface (MPS) defect to generate large local cladding deformations, which should be measureable after typical burnup times. The BISON fuel performance code is being developed at Idaho National Laboratory (INL) and is built on the Multiphysics Object-Oriented Simulation Environment (MOOSE) framework. BISON supports both 2D and 3D finite elements and solves the fully coupled equations for solid mechanics, heat conduction and species diffusion. A number of fuel performance effects are included using models for swelling, densification, creep, relocation and fission gas production & release. In addition, the mechanical and thermal contact between the fuel and cladding is explicitly modelled using a master-slave based contact algorithm. In order to accurately predict PCMI effects, the BISON code includes the relevant physics involved and provides a scalable and robust solution procedure. The depth of the proposed MPS defect is being varied in the BISON model to establish an optimum value for the experiment. The experiment will be interrupted approximately every 6 months to measure cladding radial deformation and provide data to validate BISON. The complete rodlet (~20 discrete pellets) is being simulated using a 180° half symmetry 3D model with MPS defects at two axial locations. In addition, annular pellets will be used at the top and bottom of the pellet stack to allow thermocouples within the rod to measure the fuel centerline temperature. Simulation results will be presented to illustrate the expected PCMI behavior and support the chosen experimental design parameters.

BISON↗

Analysis of Experimental Fuel Rod Parameters using 3D Modelling of PCMI with MPS Defect

An in-reactor experiment is being designed in order to validate the pellet-cladding mechanical interaction (PCMI) behavior of the BISON fuel performance code. The experimental parameters for the test rod being placed in the Halden Research Reactor are being determined using BISON simulations. The 3D model includes a missing pellet surface (MPS) defect to generate large local cladding deformations, which should be measureable after typical burnup times. The BISON fuel performance code is being developed at Idaho National Laboratory (INL) and is built on the Multiphysics Object-Oriented Simulation Environment (MOOSE) framework. BISON supports both 2D and 3D finite elements and solves the fully coupled equations for solid mechanics, heat conduction and species diffusion. A number of fuel performance effects are included using models for swelling, densification, creep, relocation and fission gas production & release. In addition, the mechanical and thermal contact between the fuel and cladding is explicitly modelled using a master-slave based contact algorithm. In order to accurately predict PCMI effects, the BISON code includes the relevant physics involved and provides a scalable and robust solution procedure. The depth of the proposed MPS defect is being varied in the BISON model to establish an optimum value for the experiment. The experiment will be interrupted approximately every 6 months to measure cladding radial deformation and provide data to validate BISON. The complete rodlet (~20 discrete pellets) is being simulated using a 180° half symmetry 3D model with MPS defects at two axial locations. In addition, annular pellets will be used at the top and bottom of the pellet stack to allow thermocouples within the rod to measure the fuel centerline temperature. Simulation results will be presented to illustrate the expected PCMI behavior and support the chosen experimental design parameters.

BISON↗

PET-FBA: A lightweight enzyme allocation and thermodynamics-constrained flux analysis approach to explore Escherichia coli metabolic adaptation to intracellular acidification

Escherichia coli employs diverse strategies to adapt to acidic environments that disrupt enzyme activity and the thermodynamic feasibility of essential reactions. To understand the impact of pH stress on cell metabolism, we present the PET-FBA (pH-, Enzyme protein allocation-, and Thermodynamics-constrained Flux Balance Analysis) framework. PET-FBA extends genome-scale modeling by integrating enzyme protein costs and reaction Gibbs free energy changes. Additionally, by incorporating pH-dependent enzyme kinetics in response to intracellular acidification, this framework enables the simulation of E. coli's metabolic adjustments across varying external pH levels. The model's accuracy is validated by comparing in silico growth simulations with experimental measurements under both anaerobic and aerobic conditions, as well as in silico gene knockouts of essential genes. By explicitly incorporating pH effects, our model accurately replicates the metabolic shift towards lactate production as the primary fermentation product at low pH in anaerobic conditions. This shift is only predicted when enzyme kinetics are dynamically adjusted as a function of pH. Further analysis revealed that this shift can be attributed to the reduced protein efficiency of the acetyl-CoA branch compared to lactate dehydrogenase under acidic stress, which then becomes crucial for maintaining NAD regeneration and cell growth at low pH. Furthermore, we identified strategies for enhancing cell growth under acidic anaerobic conditions by improving the enzyme activity of lactate dehydrogenase and pyruvate formate lyase, which increases NAD production efficiency and reduces enzyme protein allocation costs. Designed as a lightweight yet versatile framework, PET-FBA enables efficient genome-scale metabolic analysis. Using E. coli as a model system, our framework provides a systematic approach to understanding metabolic responses to environmental stress, pinpointing key metabolic bottlenecks, and identifying potential targets for strain optimization.

42 ENGINEERING↗

Tidal Stream Energy Resource Characterization in the Salish Sea

Tidal stream energy holds great potential as a renewable energy source in regions of the world where tidal currents are strong and predictable. The tidal stream energy resource of a region is strongly controlled by its tidal wave characteristics, the local bathymetry, and coastal geometric features. The Salish Sea, a large estuary on the Pacific Northwest coast, represents a great tidal stream resource because of its strong tidal currents in many tidal channels. However, the tidal resource in the Salish Sea has not been systematically characterized, primarily because of its large area and complex bathymetry and coastlines. This paper presents a modeling study conducted to characterize the tidal energy resource of the Salish Sea based on a high-resolution three-dimensional tidal hydrodynamic model of the Salish Sea, which was extensively validated using data derived from 10 tidal gauge stations and 132 Acoustic Doppler Current Profiler stations. Model validation results indicated the Salish Sea hydrodynamic model is skillful in simulating tidal wave propagation and velocity distributions in the Salish Sea. Based on model results, a total of 16 tidal channels with strong tidal currents, 9 in the San Juan Islands and Rosario Strait regions and 7 in the Puget Sound, were identified as hotspots for potential tidal energy development. Velocity probability distributions and exceedance curves of cross-channel average velocity magnitudes were calculated at all 16 channels based on the recommendations of the International Electrotechnical Commission Technical Specifications for tidal energy resource characterization. The tidal energy resource at the 16 hotspots was also characterized using power density distributions and kinetic energy fluxes. The ranking of the kinetic energy fluxes suggested that Admiralty Inlet, Rosario Strait, and Middle Channel are the top three hotspot sites in the Salish Sea for tidal stream energy development. The study demonstrated the need for a high-resolution 3-D modeling framework for accurate simulation of tidal currents in large complex estuarine systems, in the context of tidal energy resource characterization.

tidal stream energy, resource characterization, Sa↗

Fast and accurate reduced-order modeling of a MOOSE-based additive manufacturing model with operator learning

One predominant challenge in additive manufacturing (AM) is to achieve specific material properties by manipulating manufacturing process parameters during the runtime. Such manipulation tends to increase the computational load imposed on existing simulation tools employed in AM. The goal of the present work is to construct a fast and accurate reduced-order model (ROM) for an AM model developed within the Multiphysics Object-Oriented Simulation Environment (MOOSE) framework, ultimately reducing the time/cost of AM control and optimization processes. Our adoption of the operator learning (OL) approach enabled us to learn a family of differential equations produced by altering process variables in the laser’s Gaussian point heat source. More specifically, we used the Fourier neural operator (FNO) and deep operator network (DeepONet) to develop ROMs for time-dependent responses. Furthermore, we benchmarked the performance of these OL methods against a conventional deep neural network (DNN)-based ROM. Ultimately, we found that OL methods offer comparable performance and, in terms of accuracy and generalizability, even outperform DNN at predicting scalar model responses. The DNN-based ROM afforded the fastest training time. Furthermore, all the ROMs were faster than the original MOOSE model yet still provided accurate predictions. FNO had a smaller mean prediction error than DeepONet, with a larger variance for time-dependent responses. Unlike DNN, both FNO and DeepONet were able to simulate time series data without the need for dimensionality reduction techniques. Finally, the present work can help facilitate the AM optimization process by enabling faster execution of simulation tools while still preserving evaluation accuracy.

36 MATERIALS SCIENCE↗

Updates to the Generation of Physics Data Inputs for MAMMOTH Simulations of the Transient Reactor Test Facility - FY2016

The INL is currently evolving the modeling and simulation (M&S) capability that will enable improved core operation as well as design and analysis of TREAT experiments. This M&S capability primarily uses MAMMOTH, a reactor physics application being developed under Multi-physics Object Oriented Simulation Environment (MOOSE) framework. MAMMOTH allows the coupling of a number of other MOOSE-based applications. This second year of work has been devoted to the generation of a deterministic reference solution for the full core, the preparation of anisotropic diffusion coefficients, the testing of the SPH equivalence method, and the improvement of the control rod modeling. In addition, this report includes the progress made in the modeling of the M8 core configuration and experiment vehicle since January of this year.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Fusion Energy Research at Idaho National Laboratory: Experimentation and Simulation to Support Safety and Rapid Technology Development

Research into fusion energy is growing rapidly, responding to a call for sustainable sources of energy to replace fossil fuels and mitigate climate change. Within the United States, at least, researchers are also responding to the “Bold Decadal Vision” proposed by the White House, seeking to have a commercially relevant fusion pilot plant deployed within a decade. Before this can become a reality, many Fusion Science & Technology (FS&T) gaps remain. For over 45 years, Idaho National Laboratory has been at the forefront of addressing these FS&T gaps in the context of fusion safety and technology via the operation of world-leading experimental facilities within the Safety and Tritium Applied Research (STAR) Facility. Here, INL focuses on the tritium fuel cycle, conceptual system design studies, risk assessment, waste management, and materials safety. Modeling and Simulation (M&S) has also been a component of this portfolio of research, but, early on, focused on individual systems. Since 2019, active development and research on integrated whole device modeling tools based on the Multiphysics Object-Oriented Simulation Environment (MOOSE) framework has been undertaken. This has culminated in a MOOSE-based version of the Tritium Migration and Analysis Program (TMAP), an INL code historically focused on tritium permeation and trapping within fusion systems. More recently, INL Laboratory Directed Research and Development funds have been used to create the Fusion ENergy Integrated multiphys-X (FENIX) code focused on scrape-off layer plasma physics and the first wall of a magnetically confined fusion device. This talk will focus on an overview of INL activities in the FS&T research area, with a particular focus on recent M&S activities and results.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

FY22 Status Report on the ART-GCR CMVB and CNWG International Collaborations

This work presents the numerical model for the high temperature test reactor (HTTR) loss of forced cooling (LOFC) experiment with the INL codes Griffin, BISON, and RELAP-7, based on the Multiphysics Object-Oriented Simulation Environment (MOOSE) framework. Promising results were obtained, with the overall behavior of the reactor successfully captured. Changes in the heat transfer coupling, as compared to the fiscal year (FY)-21 model, enabled drastic improvement of the steady-state solution, both in terms of computational time and global energy discrepancies. The former was reduced by a factor of roughly 60, whereas the latter decreased from 11% to less than 2%. Furthermore, the discrepancy in the steady-state multiplication factor was improved from +2,300 and +2,900 pcm (for the 30 and 9 MW cases) to -700 and +1,200 pcm, respectively, and now falls well within the large measurement uncertainties stemming from graphite impurities. Validation of the Monte Carlo model used to generate cross sections was also performed against available measurements. Though significant, the discrepancies remain acceptable overall in light of the large uncertainty. Numerous improvements are still needed to better compare with the experiment involving the 9 MW case and to instill greater confidence in the model’s ability to accurately predict the 30 MW behavior. Specifically, the power levels predicted by the 9 MW transient simulation following re-criticality remain low, pointing to an underestimation of the passive cooling of the core. A key aspect of future work will be to better understand the flow pattern during the LOFC event, particularly to determine if natural or forced convection is occurring inside the reactor pressure vessel (RPV). More generally, additional validation data would be immensely useful for further enhancing the numerical model and better matching the experiments. In addition, a more sophisticated thermal-hydraulics model that simulates all the channels as a single system model should be considered to take into account the rest of the primary loop. Finally, even if the results are in better agreement with the experiments, sensitivity analysis and uncertainty quantification will be necessary to evaluate the model uncertainty.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

ETHOS: An automated framework to generate multi-fidelity constitutive data tables and propagate uncertainties to hydrodynamic simulations

Accurate constitutive data, such as equations of state and plasma transport coefficients, are necessary for reliable hydrodynamic simulations of plasma systems such as fusion targets, planets, and stars. Here, we develop a framework for automatically generating transport-coefficient tables using a parameterized model that incorporates data from both high-fidelity sources (e.g., density functional theory calculations and reference experiments) and lower-fidelity sources (e.g., average-atom and analytic models). The framework incorporates uncertainties from these multi-fidelity sources, generating ensembles of optimally diverse tables that are suitable for uncertainty quantification of hydrodynamic simulations. We illustrate the utility of the framework with magnetohydrodynamic simulations of magnetically launched flyer plates, which are used to measure material properties in pulsed-power experiments. We explore how changes in the uncertainties assigned to the multi-fidelity data sources propagate to changes in simulation outputs and find that our simulations are most sensitive to uncertainties near the melting transition. The presented framework enables computationally efficient uncertainty quantification that readily incorporates new high-fidelity measurements or calculations and identifies plasma regimes where additional data will have high impact.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Absorption Spectra of Gold Nanoparticle Suspensions

Three gold nanoparticle suspensions are obtained, and mean radii in distributions – (6.1 ± 0.2), (11.9 ± 0.3), and (17.3 ± 0.7) nm – are determined by the transmission electron microscopy method. The optical absorption spectra of suspensions are obtained and studied. Calculation of spectral dependences of the absorption index of suspensions at values of the gold complex refractive index taken from the literature showed a significant deviation of experimental and calculated data in the region of 450–800 nm. Spectral dependences of the absorption of suspensions are simulated within the framework of the Mie–Drude theory taking into account the interband absorption in the form of an additional term in the imaginary part of the dielectric permittivity of the Gaussian type. It is shown that to quantify the spectral dependences in the region of the plasmon absorption band of nanoparticles, correction of the parameters of the interband absorption is necessary in addition to the increase of the relaxation parameter of the Drude theory. Spectral dependences of the dielectric permittivity of gold in nanodimensional state are refined from the solution of the inverse problem. The results of the present work are important for predicting the special features of operation of photonic devices and optical detonators based on gold nanoparticles.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

Dayflow: CONUS Daily Streamflow Reanalysis, Version 2 (DayflowV2)

The DayflowV2 dataset provides multiple meteorologic forcings driven hourly streamflow information for approximately 2.7 million NHDPlusV2 stream reaches in the conterminous US (CONUS). DaymetV4, Stage-IV, and Analysis of Period of Record for Calibration (AORC) forcings and their corresponding hybrids drive a nationally scalable modeling framework integrating the simulated runoff from the Variable Infiltration Capacity (VIC) model with the Routing Application for Parallel computatIon of Discharge (RAPID) routing model. Streamflow with (Assimilated) and without (Naturalized) streamflow assimilation at US Geological Survey (USGS) streamflow monitoring sites are included in DayflowV2. A comprehensive evaluation of streamflow at 7,526 USGS gauges is performed for both streamflow types. The resulting key evaluation metrics are also included in the Dayflow dataset. The reanalysis data are available for variable periods; 36 years (1980-2015) for DaymetV4 (DayflowV1), 18 years (2002-2019) for Stage-IV and its hybrids, and 40 years (1980-2019) for AORC and its hybrids.

13 HYDRO ENERGY↗

Two distinct crystallization processes in supercooled liquid

Using molecular dynamics simulations we show that two distinct crystallization processes, depending on the temperature at which crystallization occurs, appear in a supercooled liquid. As a model for glass-forming materials, an Al{sub 2}O{sub 3} model system, in which both the glass transition and crystallization from the supercooled liquid can be well reproduced, is employed. Simulations in the framework of an isothermal-isobaric ensemble indicate that the calculated time-temperature-transformation curve for the crystallization to γ(defect spinel)-Al{sub 2}O{sub 3} exhibited a typical nose shape, as experimentally observed in various glass materials. During annealing above the nose temperature, the structure of the supercooled liquid does not change before the crystallization, because of the high atomic mobility (material transport). Thus, the crystallization is governed by the abrupt crystal nucleation, which results in the formation of a stable crystal structure. In contrast, during annealing below the nose temperature, the structure of the supercooled liquid gradually changes before the crystallization, and the formed crystal structure is less stable than that formed above the nose temperature, because of the restricted material transport.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Interplay of radiative and nonradiative transitions in surface hopping with radiation-molecule interactions

We implemented a method for the treatment of field induced transitions in trajectory surface hopping simulations, in the framework of the local diabatization scheme, especially suited for on-the-fly dynamics. The method is applied to a simple one-dimensional model with an avoided crossing and compared with quantum wavepacket dynamics. The results show the importance of introducing a proper decoherence correction to surface hopping, in order to obtain meaningful results. Also the energy conservation policy of standard surface hopping must be revised: in fact, the quantum wavepacket energetics is well reproduced if energy absorption/emission is allowed for in the hops determined by radiation-molecule coupling. To our knowledge, this is the first time the issues of decoherence and energy conservation have been analyzed in depth to devise a mixed quantum-classical method for dynamics with molecule-field interactions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Transportation of high-current ion and electron beams in the accelerator drift gap in the presence of an additional electron background

The dynamics of a high-current ion beam propagating in the drift gap of a linear induction accelerator with collective focusing is studied using 3D numerical simulations in the framework of the full system of the Vlasov–Maxwell equations (code KARAT). The ion beam is neutralized by a comoving electron beam in the current density and, partially, in space charge, since the velocities of electrons and ions differ substantially. The dynamics of the high-current ion beam is investigated for different versions of additional neutralization of its space charge. It is established that, for a given configuration of the magnetic field and in the presence of a specially programmed injection of additional electrons from the boundary opposite to the ion injection boundary, the angular divergence of the ion beam almost vanishes, whereas the current of the ion beam at the exit from the accelerator drift gap changes insignificantly and the beam remains almost monoenergetic.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Developing Multiphysics, Integrated, High-Fidelity, Massively Parallel Computational Capabilities for Fusion Applications Using MOOSE

As the need for fusion as a clean, sustainable, and abundant energy source grows internationally, so does the need for multiphysics, computational tools to model, study, and predict the complex interactions between plasma, materials, and engineering processes. These tools have a crucial role to play in solving scientific and engineering challenges and accelerating fusion energy deployment. To address these needs, modeling capabilities should enable massively parallel, multiphysics, fully integrated high-fidelity simulations of fusion systems. Additional attributes, such as being open source and modular while maintaining high software quality assurance standards will maximize impact by ensuring accessibility for all and wide acceptance, rapid expansion and development, as well as reliability, efficiency, and robustness. In this paper, we describe how the Multiphysics Object-Oriented Simulation Environment (MOOSE) framework, which has a track record of success in the fission space thanks to the attributes listed above, can be leveraged in the fusion energy field. We highlight key successes of the MOOSE application in the fission space and describe how MOOSE has been and is being applied to fusion applications in the United States---e.g., Tritium Migration Analysis Program, version 8 (TMAP8), MOOSE Fusion Module, Fusion ENergy Integrated multiphys-X (FENIX)---and the United Kingdom---e.g., AURORA, Achlys, Apollo. These efforts aim to establish a suite of tools that can be further extended to accelerate fusion energy deployment.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Impact of geometric, thermal and tunneling effects on nano-transistors

Electronic transistors are fundamental building blocks of large scale integrated circuits in modern advanced electronic equipments, and their sizes have been down-scaled to nanometers. Modeling and simulations in the framework of quantum dynamics have emerged as important tools to study functional characteristics of these nano-devices. This work explores the effects of geometric shapes of semiconductor–insulator interfaces, phonon–electron interactions, and quantum tunneling of three-dimensional (3D) nano-transistors. First, we propose a two-scale energy functional to describe the electron dynamics in a dielectric continuum of device material. Coupled governing equations, i.e., Poisson–Kohn–Sham (PKS) equations, are derived by the variational principle. Additionally, it is found that at a given channel cross section area and gate voltage, the geometry that has the smallest perimeter of the channel cross section offers the largest channel current, which indicates that ultra-thin nanotransistors may not be very efficient in practical applications. Moreover, we introduce a new method to evaluate quantum tunneling effects in nanotransistors without invoking the comparison of classical and quantum predictions. It is found that at a given channel cross section area and gate voltage, the geometry that has the smallest perimeter of the channel cross section has the smallest quantum tunneling ratio, which indicates that geometric defects can lead to higher geometric confinement and larger quantum tunneling effect. Furthermore, although an increase in the phonon–electron interaction strength reduces channel current, it does not have much impact to the quantum tunneling ratio. Finally, advanced numerical techniques, including second order elliptic interface methods, have been applied to ensure computational accuracy and reliability of the present PKS simulation.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Vortex and Sink Flows in Eruptive Flares as a Model for Coronal Implosions

Eruptive flares are sudden releases of magnetic energy that involve many phenomena, several of which can be explained by the standard 2D flare model and its realizations in 3D. We analyze a 3D magnetohydrodynamics simulation, in the framework of this model, that naturally explains the contraction of coronal loops in the proximity of the flare sites, as well as the inflow toward the region above the cusp-shaped loops. We find that two vorticity arcs located along the flanks of the erupting magnetic flux rope are generated as soon as the eruption begins. The magnetic arcades above the flux rope legs are then subjected to expansion, rotation, or contraction depending on which part of the vortex flow advects them. In addition to the vortices, an inward-directed magnetic pressure gradient exists in the current sheet below the magnetic flux rope. It results in the formation of a sink that is maintained by reconnection. We conclude that coronal loop apparent implosions observed during eruptive flares are the result of hydromagnetic effects related to the generation of vortex and sink flows when a flux rope moves in a magnetized environment.

79 ASTRONOMY AND ASTROPHYSICS↗

Avoiding pitfalls in molecular simulation of vapor sorption: Example of propane and isobutane in metal–organic frameworks for adsorption cooling applications

This study introduces recommendations for conducting molecular simulations of vapor adsorption, with an emphasis on enhancing the accuracy, reproducibility, and comparability of results. The first aspect we address is consistency in the implementation of some details of typical molecular models, including tail corrections and cutoff distances, due to their significant influence on generated data. We highlight the importance of explicitly calculating the saturation pressures at relevant temperatures using methods such as Gibbs ensemble Monte Carlo simulations and illustrate some pitfalls in extrapolating saturation pressures using this method. For grand canonical Monte Carlo (GCMC) simulations, the input fugacity is usually calculated using an equation of state, which often requires the critical parameters of the fluid. We show the importance of using critical parameters derived from the simulation with the same model to ensure internal consistency between the simulated explicit adsorbate phase and the implicit bulk phase in GCMC. We show the advantages of presenting isotherms on a relative pressure scale to facilitate easier comparison among models and with experiment. Extending these guidelines to a practical case study, we evaluate the performance of various isoreticular metal–organic frameworks (MOFs) in adsorption cooling applications. This includes examining the advantages of using propane and isobutane as working fluids and identifying MOFs with a superior performance.

36 MATERIALS SCIENCE↗