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At least 1,315 records · Page 73

Advanced Fuels Campaign Execution Plan

The Advanced Fuels Campaign (AFC) Execution Plan details the strategy, mission, scope, and goals—both near-term and long-term—along with the structure and organization of nuclear fuels and materials research, development, and demonstration (RD&D) activities within the Fuel Cycle Technologies (FCT) program. The FCT program, tasked by the U.S. Department of Energy (DOE), employs a science-based approach to advance fuel technologies. This approach integrates theory, experiments, and multi-scale modeling and simulation (M&S) to develop a predictive understanding of fuel fabrication processes and fuel/cladding performance under irradiation, moving beyond traditional empirical methods. The long-term goals of the AFC are guided by the AFC Strategic Plan and align with the DOE Office of Nuclear Energy (NE) Roadmap [1], which outlines a multi-decade vision for demonstrating and qualifying advanced fuel forms to support diverse fuel cycle options. Near-term goals focus on enhancing accident tolerant fuels (ATF) for Light Water Reactors (LWR), a significant challenge that demands balancing immediate objectives with ongoing progress toward advanced reactor missions. Accelerating the traditional fuel qualification process to meet ATF objectives is another critical challenge. A detailed set of 5-year goals, summarized below, has been developed in line with the overarching science-based fuel development approach: • Advanced LWR Fuel Technologies: By 2027, support the development of advanced LWR fuel technologies with improved performance and enhanced accident tolerance. This includes high burnup (HBu), low enriched uranium (LEU)+, coated cladding, and doped fuel, aimed at complementing industry-led significant LWR uprates and plant refurbishments. • Tristructural Isotropic (TRISO) Fuel: Achieve qualification by 2028 and develop improved designs for emerging markets. • Metal Fuel: Achieve qualification by 2028 and develop improved designs for emerging markets. • Molten Salt Fuel: By 2027, deploy a robust program that enables fuel salt qualification technologies needed to support fuel salt research and development (R&D), focusing on emergent needs to derisk fuel salt production and utilization in advanced reactors. • Long-Term ATF: Develop fuel technologies that enable significant power uprates (~50%) in refurbished or new LWRs while optimizing fissile material utilization and waste disposal. The 5-year milestones in the AFC Execution Plan are contingent on an assumed budget. This Execution Plan will be updated annually to reflect actual funding profiles as budget guidance becomes available, ensuring milestones are adjusted accordingly. In summary, the AFC Execution Plan presents a comprehensive strategy to advance nuclear fuel technologies through a science-based approach, addressing both near-term and long-term goals while adapting to funding realities.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Fermilab Booster loss modelling and rebalancing using Bayesian methods

Fermilab Booster is being upgraded for the PIP-II project to support 20Hz ramp rate at higher intensities. Loss trip limits determine the achievable peak power. To meet PIP-II requirements, losses need to be halved as compared to current levels. Losses primarily occur at injection and transition crossing, with both gradually increasing and threshold-like intensity-dependent behaviors. The existing simulation models are not yet good enough for quantitative loss predictions. In practice, it will be necessary to tune up the Booster using iterative methods and operator intuition. In this paper we present an effort to systematically model Booster losses using active learning (Bayesian exploration) techniques, and subsequently to rebalance them for higher trip limit margins. We first created several sets of spatially and temporally isolated orbit and optics knobs, and trained Gaussian process models for each beam loss monitor as well as beam current. This is a complex task due to safety and timing requirements – we discuss mitigations such as uncertainty constraints and approximate fitting. Once models are stable, we perform large-scale single and multi-objective tuning using scalarized objectives made up of critical beam loss locations. Our results demonstrate significant rebalancing of losses, increasing trip margins, as well as an overall improvement in beam transmission efficiency. We are exploring how to combine existing simulations with experimental data and automate the collection procedure so that more advanced surrogate models can be created over time.

Kuklev, Nikita [Fermilab]↗

Bridging Scales in Bioenergy and Catalysis: A Review of Mesoscale Modeling Applications, Methods, and Future Directions

Between the molecular and reactor scales, which are familiar to the chemical engineering community, lies an intermediate regime, here termed the “mesoscale,” where transport phenomena and reaction kinetics compete on similar time scales. Bioenergy and catalytic processes offer particularly important examples of mesoscale phenomena owing to their multiphase nature and the complex, highly variable porosity characteristic of biomass and many structured catalysts. In this review, we overview applications and methods central to mesoscale modeling as they apply to reaction engineering of biomass conversion and catalytic processing. A brief historical perspective is offered to put recent advances in context. Applications of mesoscale modeling are described, and several specific examples from biomass pyrolysis and catalytic upgrading of bioderived intermediates are highlighted. Methods including reduced order modeling, finite element and finite volume approaches, geometry construction and import, and visualization of simulation results are described; in each category, recent advances, current limitations, and areas for future development are presented. Owing to improved access to high-performance computational resources, advances in algorithm development, and sustained interest in reaction engineering to sustainably meet societal needs, we conclude that a significant upsurge in mesoscale modeling capabilities is on the horizon that will accelerate design, deployment, and optimization of new bioenergy and catalytic technologies.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Monte Carlo Simulation of Borosilicate Glass Dissolution using Molecular Dynamics-Generated Glass Structures

Atomic-scale insights into the dissolution mechanisms of borosilicate glasses are critical to the development of the waste form corrosion models that inform performance assessments of nuclear waste disposal facilities. Monte Carlo (MC) simulations have been instrumental in advancing the state of knowledge of borosilicate glass dissolution; however, all such simulations to date have relied on lattices to represent the amorphous glass structure, thereby potentially introducing artifacts. Therefore, a new approach, referred to as the amorphous MC approach, has been developed whereby glass structures generated from molecular dynamics simulations are used as starting points for MC simulations of glass dissolution. MC simulations of sodium borosilicate glasses that covered a wide compositional range were performed and revealed correlations between dissolution rate and structural features of the glasses. Notably, the lattice MC approach predicted the fraction of tetrahedral boron to have a lesser influence on the dissolution rate than computed with the amorphous MC approach. The lattice MC simulations also overestimated the dissolution rate for a given glass composition. These findings highlight the importance of using truly amorphous structures in MC simulations of glass corrosion.

Kerisit, Sebastien N.↗

An error-controlled adaptive time-stepping method for particle advancement in coupled CFD-DEM simulations

Coupled Computational-Fluid-Dynamics (CFD) and Discrete-Element-Method (DEM) models provide an accurate description of multiphase physical systems where a solid granular particle phase exists in an underlying gaseous continuous medium. The time integration of the granular phase in these simulations is typically handled using an explicit scheme with a constant time-step among all particles that is invariant in time to resolve inter-particle collisions. A locally third-order accurate adaptive time integration technique for particles that employs an embedded locally second-order scheme for error determination is presented in this work. The particle time-step size is dynamically adapted based on solution error, thus leading to significant savings in computational time. The efficacy of our scheme is quantified using four test cases of varying complexity (binary collision, homogeneous cooling system, fluidized bed and hopper discharge). The adaptive time-stepping method exhibits improved performance (~ 2–3 times in most of the cases studied) compared to three commonly used non-adaptive time-step methods (first-order Euler-explicit, second-order Adams-Bashforth and third-order Runge-Kutta schemes), while maintaining the same level of accuracy and parallel scalability.

42 ENGINEERING↗

Advanced Turbulence Models for Large-Scale Atmospheric Boundary Layer Flows

We present high-fidelity large-eddy-simulation (LES) modeling approaches for the turbulent atmospheric boundary layer (ABL) flows. Wind energy is a prime example of an application driven by ABL. Generation of electrical energy from farms of wind turbines at night in the stable ABL is a particularly interesting situation. In this report, we consider the well-known GEWEX (Global Energy and Water Cycle Experiment) Atmospheric Boundary Layer Study (GABLS) stably stratified benchmark LES case. We use a high-order spectral element code Nek5000/RS, which is supported under the DOE's Exascale Computing Project (ECP) Center for Efficient Exascale Discretizations (CEED) project, targeting application simulations on various acceleration-device based exascale computing platforms. In our earlier ANL report, we demonstrated our newly developed subgrid-scale (SGS) models based on high-pass filter (HPF), mean-field eddy viscosity (MFEV), and Smagorinsky (SMG) with no-slip and traction boundary conditions, provided with low-order statistics, convergence and turbulent structure analysis. In this report, we extend the range of our SGS modeling approaches in the context of the mean-field eddy viscosity (MFEV), to include the solution of an SGS turbulent kinetic energy equation (TKE). We demonstrate the model fidelity of Nek5000/RS in comparison to that of AMR-Wind, a block-structured second-order finite-volume code with adaptive-mesh-refinement capabilities, with which we studied scaling performance for both codes in comparison on DOE's leadership computing platforms.

17 WIND ENERGY↗

Challenges of NDE Simulation Tool Challenges of NDE Simulation Tool

Realistic nondestructive evaluation (NDE) simulation tools enable inspection optimization and predictions of inspectability for new aerospace materials and designs. NDE simulation tools may someday aid in the design and certification of advanced aerospace components; potentially shortening the time from material development to implementation by industry and government. Furthermore, modeling and simulation are expected to play a significant future role in validating the capabilities and limitations of guided wave based structural health monitoring (SHM) systems. The current state-of-the-art in ultrasonic NDE/SHM simulation cannot rapidly simulate damage detection techniques for large scale, complex geometry composite components/vehicles with realistic damage types. This paper discusses some of the challenges of model development and validation for composites, such as the level of realism and scale of simulation needed for NASA' applications. Ongoing model development work is described along with examples of model validation studies. The paper will also discuss examples of the use of simulation tools at NASA to develop new damage characterization methods, and associated challenges of validating those methods.

Leckey, Cara A. C.↗

Field Validated Utility-Scale Battery Storage Control Models for Quasi-Static Analyses

This paper presents a co-simulation based approach to implement and validate advanced battery storage control modes in OpenDSS that replicate behavior of a utility scale vanadium red-ox flow battery (VRFB). Inverter-interfaced utiliy-scale battery storage systems (BSS) have modes of operation to facilitate multiple grid-support functions. In order to enable accurate understanding of the impacts from grid-support functions modes of operation it is required to develop validated models that replicates behavior of the actual control system. This paper presents the pseudo code for the implemented control schemes including peak shaving and capacity firming control modes. Additionally, this paper also provides insight on convergence sensitivity of the presented algorithms to related parameters. The results obtained from simulation studies will be compared against field operated utility-scale BSS measurements to verify the implemented algorithms.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Progress in Modeling and Simulation of Batteries

Modeling and simulation of batteries, in conjunction with theory and experiment, are important research tools that offer opportunities for advancement of technologies that are critical to electric motors. The development of data from the application of these tools can provide the basis for managerial and technical decision-making. Together, these will continue to transform batteries for electric vehicles. This collection of nine papers presents the modeling and simulation of batteries and the continuing contribution being made to this impressive progress, including topics that cover: * Thermal behavior and characteristics * Battery management system design and analysis * Moderately high-fidelity 3D capabilities * Optimization Techniques and Durability As electric vehicles continue to gain interest from manufacturers and consumers alike, improvements in economy and affordability, as well as adoption of alternative fuel sources to meet government mandates are driving battery research and development. Progress in modeling and simulation will continue to contribute to battery improvements that deliver increased power, energy storage, and durability to further enhance the appeal of electric vehicles.

batteries↗

Biomembrane Structure and Material Properties Studied With Neutron Scattering

Cell membranes and their associated structures are dynamical supramolecular structures where different physiological processes take place. Detailed knowledge of their static and dynamic structures is therefore needed, to better understand membrane biology. The structure–function relationship is a basic tenet in biology and has been pursued using a range of different experimental approaches. In this review, we will discuss one approach, namely the use of neutron scattering techniques as applied, primarily, to model membrane systems composed of lipid bilayers. An advantage of neutron scattering, compared to other scattering techniques, is the differential sensitivity of neutrons to isotopes of hydrogen and, as a result, the relative ease of altering sample contrast by substituting protium for deuterium. This property makes neutrons an ideal probe for the study of hydrogen-rich materials, such as biomembranes. In this review article, we describe isotopic labeling studies of model and viable membranes, and discuss novel applications of neutron contrast variation in order to gain unique insights into the structure, dynamics, and molecular interactions of biological membranes. We specifically focus on how small-angle neutron scattering data is modeled using different contrast data and molecular dynamics simulations. We also briefly discuss neutron reflectometry and present a few recent advances that have taken place in neutron spin echo spectroscopy studies and the unique membrane mechanical data that can be derived from them, primarily due to new models used to fit the data.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Implementation and Validation of a Generalized Actuator Disk Parameterization for Wind Turbine Simulations Within the FastEddy Model

ABSTRACT Fast and accurate large‐eddy simulation (LES) of the atmospheric boundary layer plays a crucial role in advancing wind energy research. Long‐duration wind farm studies at turbine‐resolving scales have become increasingly important to understand the intricate interactions between large wind farms and the atmospheric boundary layer. However, the prohibitive computational cost of these turbulence‐ and turbine‐resolving simulations has precluded such modeling to be exercised on a regular basis. To that end, we implement and validate the generalized actuator disk (GAD) model in the computationally efficient, graphics processing unit (GPU)–resident, LES model FastEddy. We perform single‐turbine simulations under three atmospheric stabilities (neutral, unstable, and stable) and compare them against observations from the Scaled Wind Farm Technology (SWiFT) facility and other LES codes from the recent Wakebench turbine wake model benchmark. Our idealized LES results agree well with observed wake velocity deficit and downstream recovery across stability regimes. Turbine response in terms of rotational speed, generated power, torque, and thrust coefficient are well predicted across stability regimes and are consistent with the LES results from the benchmark. The FastEddy simulations are found to be at least two orders of magnitude more efficient than the traditional CPU‐based LES models, opening the door for realistic LES simulations of full wind plants as a viable standard practice.

17 WIND ENERGY↗

Predicting Near-Term Changes in the Earth System: A Large Ensemble of Initialized Decadal Prediction Simulations Using the Community Earth System Model

The objective of near-term climate prediction is to improve our fore-knowledge, from years to a decade or more in advance, of impactful climate changes that can in general be attributed to a combination of internal and externally forced variability. Predictions initialized using observations of past climate states are tested by comparing their ability to reproduce past climate evolution with that of uninitialized simulations in which the same radiative forcings are applied. A new set of decadal prediction (DP) simulations has recently been completed using the Community Earth System Model (CESM) and is now available to the community. This new large-ensemble (LE) set (CESM-DPLE) is composed of historical simulations that are integrated forward for 10 years following initialization on 1 November of each year between 1954 and 2015. CESM-DPLE represents the “initialized” counterpart to the widely studied CESM Large Ensemble (CESM-LE); both simulation sets have 40-member ensembles, and they use identical model code and radiative forcings. Comparing CESM-DPLE to CESM-LE highlights the impacts of initialization on prediction skill and indicates that robust assessment and interpretation of DP skill may require much larger ensembles than current protocols recommend. CESM-DPLE exhibits significant and potentially useful prediction skill for a wide range of fields, regions, and time scales, and it shows widespread improvement over simpler benchmark forecasts as well as over a previous initialized system that was submitted to phase 5 of the Coupled Model Intercomparison Project (CMIP5). Finally, the new DP system offers new capabilities that will be of interest to a broad community pursuing Earth system prediction research.

54 ENVIRONMENTAL SCIENCES↗

RVA: A Plugin for ParaView 3.14

RVA is a plugin developed for the 64-bit Windows version of the ParaView 3.14 visualization package. RVA is designed to provide support in the visualization and analysis of complex reservoirs being managed using multi-fluid EOR techniques. RVA, for Reservoir Visualization and Analysis, was developed at the University of Illinois at Urbana-Champaign, with contributions from the Illinois State Geological Survey, Department of Computer Science and National Center for Supercomputing Applications. RVA was designed to utilize and enhance the state-of-the-art visualization capabilities within ParaView, readily allowing joint visualization of geologic framework and reservoir fluid simulation model results. Particular emphasis was placed on enabling visualization and analysis of simulation results highlighting multiple fluid phases, multiple properties for each fluid phase (including flow lines), multiple geologic models and multiple time steps. Additional advanced functionality was provided through the development of custom code to implement data mining capabilities. The built-in functionality of ParaView provides the capacity to process and visualize data sets ranging from small models on local desktop systems to extremely large models created and stored on remote supercomputers. The RVA plugin that we developed and the associated User Manual provide improved functionality through new software tools, and instruction in the use of ParaView-RVA, targeted to petroleum engineers and geologists in industry and research. The RVA web site (http://rva.cs.illinois.edu) provides an overview of functions, and the development web site (https://github.com/shaffer1/RVA) provides ready access to the source code, compiled binaries, user manual, and a suite of demonstration data sets. Key functionality has been included to support a range of reservoirs visualization and analysis needs, including: sophisticated connectivity analysis, cross sections through simulation results between selected wells, simplified volumetric calculations, global vertical exaggeration adjustments, ingestion of UTChem simulation results, ingestion of Isatis geostatistical framework models, interrogation of joint geologic and reservoir modeling results, joint visualization and analysis of well history files, location-targeted visualization, advanced correlation analysis, visualization of flow paths, and creation of static images and animations highlighting targeted reservoir features.

Source record↗

RVA. 3-D Visualization and Analysis Software to Support Management of Oil and Gas Resources

A free software application, RVA, has been developed as a plugin to the US DOE-funded ParaView visualization package, to provide support in the visualization and analysis of complex reservoirs being managed using multi-fluid EOR techniques. RVA, for Reservoir Visualization and Analysis, was developed as an open-source plugin to the 64 bit Windows version of ParaView 3.14. RVA was developed at the University of Illinois at Urbana-Champaign, with contributions from the Illinois State Geological Survey, Department of Computer Science and National Center for Supercomputing Applications. RVA was designed to utilize and enhance the state-of-the-art visualization capabilities within ParaView, readily allowing joint visualization of geologic framework and reservoir fluid simulation model results. Particular emphasis was placed on enabling visualization and analysis of simulation results highlighting multiple fluid phases, multiple properties for each fluid phase (including flow lines), multiple geologic models and multiple time steps. Additional advanced functionality was provided through the development of custom code to implement data mining capabilities. The built-in functionality of ParaView provides the capacity to process and visualize data sets ranging from small models on local desktop systems to extremely large models created and stored on remote supercomputers. The RVA plugin that we developed and the associated User Manual provide improved functionality through new software tools, and instruction in the use of ParaView-RVA, targeted to petroleum engineers and geologists in industry and research. The RVA web site (http://rva.cs.illinois.edu) provides an overview of functions, and the development web site (https://github.com/shaffer1/RVA) provides ready access to the source code, compiled binaries, user manual, and a suite of demonstration data sets. Key functionality has been included to support a range of reservoirs visualization and analysis needs, including: sophisticated connectivity analysis, cross sections through simulation results between selected wells, simplified volumetric calculations, global vertical exaggeration adjustments, ingestion of UTChem simulation results, ingestion of Isatis geostatistical framework models, interrogation of joint geologic and reservoir modeling results, joint visualization and analysis of well history files, location-targeted visualization, advanced correlation analysis, visualization of flow paths, and creation of static images and animations highlighting targeted reservoir features.

97 MATHEMATICS AND COMPUTING↗

RVA: A Plugin for ParaView 3.14

RVA is a plugin developed for the 64-bit Windows version of the ParaView 3.14 visualization package. RVA is designed to provide support in the visualization and analysis of complex reservoirs being managed using multi-fluid EOR techniques. RVA, for Reservoir Visualization and Analysis, was developed at the University of Illinois at Urbana-Champaign, with contributions from the Illinois State Geological Survey, Department of Computer Science and National Center for Supercomputing Applications. RVA was designed to utilize and enhance the state-of-the-art visualization capabilities within ParaView, readily allowing joint visualization of geologic framework and reservoir fluid simulation model results. Particular emphasis was placed on enabling visualization and analysis of simulation results highlighting multiple fluid phases, multiple properties for each fluid phase (including flow lines), multiple geologic models and multiple time steps. Additional advanced functionality was provided through the development of custom code to implement data mining capabilities. The built-in functionality of ParaView provides the capacity to process and visualize data sets ranging from small models on local desktop systems to extremely large models created and stored on remote supercomputers. The RVA plugin that we developed and the associated User Manual provide improved functionality through new software tools, and instruction in the use of ParaView-RVA, targeted to petroleum engineers and geologists in industry and research. The RVA web site (http://rva.cs.illinois.edu) provides an overview of functions, and the development web site (https://github.com/shaffer1/RVA) provides ready access to the source code, compiled binaries, user manual, and a suite of demonstration data sets. Key functionality has been included to support a range of reservoirs visualization and analysis needs, including: sophisticated connectivity analysis, cross sections through simulation results between selected wells, simplified volumetric calculations, global vertical exaggeration adjustments, ingestion of UTChem simulation results, ingestion of Isatis geostatistical framework models, interrogation of joint geologic and reservoir modeling results, joint visualization and analysis of well history files, location-targeted visualization, advanced correlation analysis, visualization of flow paths, and creation of static images and animations highlighting targeted reservoir features.

Source record↗

Dynamic response tests of inertial and optical wind-tunnel model attitude measurement devices

Results are presented for an experimental study of the response of inertial and optical wind-tunnel model attitude measurement systems in a wind-off simulated dynamic environment. This study is part of an ongoing activity at the NASA Langley Research Center to develop high accuracy, advanced model attitude measurement systems that can be used in a dynamic wind-tunnel environment. This activity was prompted by the inertial model attitude sensor response observed during high levels of model vibration which results in a model attitude measurement bias error. Significant bias errors in model attitude measurement were found for the measurement using the inertial device during wind-off dynamic testing of a model system. The amount of bias present during wind-tunnel tests will depend on the amplitudes of the model dynamic response and the modal characteristics of the model system. Correction models are presented that predict the vibration-induced bias errors to a high degree of accuracy for the vibration modes characterized in the simulated dynamic environment. The optical system results were uncorrupted by model vibration in the laboratory setup.

Buehrle, R. D.↗

Using Metadynamics to Reveal Extractant Conformational Free Energy Landscapes

Understanding the impact of extractant functionalization on metal-binding energetics in liquid-liquid extraction is essential to guide the development of better separation processes. Traditionally, computational extractant design uses electronic structure calculations on metal-ligand clusters to determine the metal-binding energy of the lowest energy state. Although highly accurate, this approach does not account for all of the relevant physics encountered under experimental conditions. Such methodologies often neglect entropic contributions such as temperature effects and ligand flexibility, in addition to approximating solvent-extractant interactions with implicit solvent models. In this study, we use classical molecular dynamics simulations with an advanced sampling method, metadynamics, to map out extractant molecule conformational free energies in the condensed phase. Here we generate the complete conformational landscape in solution for a family of bidentate malonamide-based extractants with different functionalizations of the headgroup and the side chains. In particular, we show how such alkyl functionalization reshapes the free energy landscape, affecting the free energy penalty of organizing the extractant into the cis-like metal-binding conformation from the trans-like conformation of the free extractant in solution. Specifically, functionalizing alkyl tails to the center of the headgroup has a greater influence on increasing molecular rigidity and disfavoring the binding conformation than functionalizing side chains. These findings are consistent with trends in metal-binding energetics based on experimentally reported distribution ratios. We also consider a different bidentate extractant molecule, carbamoylmethylphosphine oxide, and show how the choice of solvent can further reshape the conformational energetic landscape. This study demonstrates the feasibility of using molecular dynamics simulations with advanced sampling techniques to investigate extractant conformational energetics in solution, which, more broadly, will enable extractant design that accounts for entropic effects and explicit solvation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A new dump system design for stray light reduction of Thomson scattering diagnostic system on EAST

Thomson scattering (TS) diagnostic is an important diagnostic for measuring electron temperature and density during plasma discharge. However, the measurement of Thomson scattering signal is disturbed by the stray light easily. The stray light sources in the Experimental Advanced Superconducting Tokamak (EAST) TS diagnostic system were analyzed by a simulation model of the diagnostic system, and simulation results show that the dump system is the primary stray light source. Based on the optics theory and the simulation analysis, a novel dump system including an improved beam trap was proposed and installed. The measurement results indicate that the new dump system can reduce more than 60% of the stray light for the diagnostic system, and the influence of stray light on the error of measured density decreases.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗