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At least 613 records · Page 34
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

VERIFICATION OF TRISO FUEL BURNUP USING MACHINE LEARNING ALGORITHMS

Pebble Bed Reactors are fueled with fuel pebbles that are circulated multiple times through the reactor vessel before discharge. During the normal operation of a PBR, ejected pebbles are returned to the reactor or discharged depending on the fuel burnup and physical condition of the pebbles. The burnup measurement is usually based on detected radiation signatures of fission products accumulated in the pebble fuel over burnup. Previous research has shown that height of photopeaks of fission products, such as 134Cs, 137Cs, 154Eu, etc., can be used independently or in combination to infer or predict the level of burnup in the fuel. However, it remains challenging to measure such complex sources due to self-shielding effects, strong radiation background and intervening materials. Another operational challenge is the required high throughput of burnup measurement, which necessitates limited measurement time and thus impacts quality of measured gamma-ray spectra. Hence, advanced spectral analysis methods are needed to analyze the noisy gamma spectra and predict the burnup values. We propose to use machine learning (ML) method to interpret gamma-ray spectra and predict the burnup values of the pebbles. ML has achieved widespread success and adoption across a few domains that require pattern recognition and analysis in varied data types. In this work, we apply three proven ML approaches - multilayer perceptrons, convolutional neural networks, and transformers - to the task of predicting fuel burnup from measured gamma spectra, and compile a dataset of simulated spectra for training and validation of the ML models. In this paper, we will discuss the network architecture of these three ML approaches and compare the performance of the simplest of these (MLP) to a standard linear regression.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2023

Data Driven Approach to Dislocation-Based Plasticity Models of Face-Centered Cubic Metals

Dislocation dynamics controls plastic deformation, mechanical strength, and failure of crystalline materials. It also governs fatigue resistance under cyclic loading, creep resistance at elevated-temperature, and radiation resistance for reactor applications. There is a compelling need for understanding fundamental dislocation mechanisms for deformation because virtually all structural metals used in energy systems are fabricated to desired forms and shapes by deformation processes. To date, the most outstanding problem in a physics-based multiscale model of crystal plasticity is the lack of quantitative connections between continuum plasticity (CP) models with the lower scale dislocation models. As a result, existing CP models used in engineering applications are still phenomenological, while evidence continues to mount that they can make inaccurate predictions under realistically complex scenarios. This project takes advantage of the recent advances in high-performance discrete dislocation dynamics (DDD) simulations and data science approaches to establish the first fully connected multiscale plasticity model for pure face-centered cubic (FCC) single crystals.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Measurement of Fission Product Concentration Profiles in AGR-3/4 TRISO Fuel Graphitic Matrix and Nuclear Graphites

The third Advanced Gas Reactor (AGR) irradiation experiment, AGR-3/4, was designed to investigate the migration of fission products in fuel compact graphitic matrix and reactor graphite components. Using destructive methods, radial fission product concentration profiles were measured for gamma-emitting fission products (e.g., Ag-110m, Cs-134, and Eu-154) and beta-emitting Sr-90 in irradiated graphitic and graphite components from six different AGR-3/4 irradiation capsules. These new measured concentration profiles can now be compared to non-destructive measurements and fission product transport simulations and will be used to derive new diffusivities and sorptivities to support refinement of fission product transport models and high-temperature gas-cooled reactor (HTGR) source-term analyses. Each capsule in the AGR-3/4 experiment had four fuel compacts in the middle of two concentric rings of graphitic matrix material, PCEA graphite, or IG-110 graphite. In addition to the approximately 1898 tristructural isotropic (TRISO) coated particles in each compact, there were 20 designed to fail (DTF) particles coated only in pyrocarbon so that they released fission products into the surrounding cylindrical rings of carbonaceous materials. Destructive sampling of the rings involved machining/milling material from around the circumference of the rings, collecting that material, and performing radiochemical analyses on it. Milling operations were performed in multiple steps or segments, and each segment was generally 0.508 mm (0.020 in) thick. Knowing the radial position at which each segment was milled, the volume of the milled material at each segment, and the fission product content in each segment, the radial fission product concentrations were constructed for select isotopes in each ring. Ag-110m profiles had the most variation. Some profiles were peaked at an inner or outer surface. Some were peaked at the middle of the ring wall thickness. Some increased radially outward, and some decreased radially outward. These types of variations and the fact that the measured profiles do not generally compare favorably with the transport model employed for AGR-3/4 may adversely impact the ability to extract reasonable transport parameters for this isotope. In many cases, the Cs-134 profiles decreased somewhat linearly in the outward radial direction, and in cursory comparisons, the shapes of these profiles appeared similar to those from model predictions. The step changes in concentration across the inner-outer ring gap were generally consistent with the model predictions as well. In some cases, there were local maxima in concentration at the outer surface of the rings. This suggests that fission products could have transported in the small gaps between the inner ring and the outer ring and between the outer ring and the sink ring such that some portion of a given fission product can bypass diffusion through the ring itself. The analysis of the small nubs on the outer surfaces of some of the outer rings revealed fission product concentrations in the nubs that were often higher than in the outermost segments of the rings. This further supports the hypothesis that short-circuit, gap transport occurred, causing relatively high surface concentrations on the outer surfaces of the rings. Eu-154 and Sr-90 profiles tend to have very similar shapes, suggesting that they transport via the same mechanisms. The observed profiles were indicative of a transport process where the isotopes are sorbed on the inner surface of the ring, but diffusion into the ring from that surface is quite slow. Some elevated concentrations of Sr-90 (relative to Eu-154) on the outer surface of a ring suggested that rapid, gas-gap transport of gaseous precursor Kr-90 and volatile Rb-90 could have occurred prior to their decaying to Sr-90. Overall, the Eu 154 and Sr-90 profiles were still very similar, which indicates that the transport of short-lived Sr-90 precursors is not a major effect. In some capsules, the qualitative Sr-90 behavior across the ring gaps was consistent with the model (using the available legacy Sr-90 transport parameters), but in other capsules the model was inconsistent with the measurements and seems to underestimate the amount of Sr-90 in the outer rings. The total ring Sr-90 inventories were estimated for all the rings that were subject to physical sampling. These results will be used to adjust the predicted particle and/or compact releases used in the AGR-3/4 fission product transport model. Given the different irradiation temperatures among the capsules and the rings, it was not possible to discern fundamental differences in the transport of isotopes within the different carbon materials, i.e., graphitic matrix, IG-110, or PCEA. It may be possible to do this in the course of determining transport from the concentration profiles in future work.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Computing the solubility of argon and xenon in molten sodium chloride and potassium chloride salts

Molten salt reactors (MSRs) offer significant advancements in nuclear reactor safety and efficiency by operating at higher temperatures and lower pressures compared to traditional reactors. A critical aspect of MSR operation involves understanding the solubility of fission byproducts, particularly noble gases, in the molten salts used. This study employs molecular dynamics (MD) simulations to compute Henry’s law constants and enthalpies of solvation for argon and xenon in molten sodium chloride (NaCl) and potassium chloride (KCl). We developed a new pairwise potential for the noble gas and salt interactions based on first principles calculations. We then used this potential to calculate Henry’s law constants of the two gases in the molten salts, which were modeled using both a rigid ion model (RIM) and a polarizable ion model (PIM). The solubility calculations, performed using the Widom insertion method, show qualitative agreement with limited experimental data, highlighting the temperature dependence and greater solubility of both gases in KCl compared to NaCl. Additionally, free volume analysis elucidated the role of available space within the molten salts in governing solubility trends. Our findings suggest that PIM trajectories provide more reliable predictions for noble gas solubility than RIM due to their accurate density representation. Furthermore, these results enhance understanding of gas solubility in MSR environments, and the methods can be readily extended to other systems.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Nek5000: improvements in the available RANS models, meshing, tutorials, and training

This year, the Nuclear Energy Advanced Modeling Simulation program (NEAMS) thermal-hydraulics report for Nek5000 NRC- and verification and validation (V&V)-driven development focuses on following areas of code application and improvement. First we have continued improvements of RANS modeling capabilities in Nek5000 including improved k-tau model focusing mostly on wallfunction initial implementation with spectral element method (SEM) and initiating investigation of an alternative approach XSEM that greatly reduces discretization errors.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

High-Burnup BWR LOCA Burst Analysis Using High-Fidelity Multiphysics Simulations

The US nuclear industry is looking to improve on the operating economics of the current fleet of light-water reactors (LWRs). One way of achieving this is by operating fuel to higher burnup. In pressurized water reactors (PWRs), relaxing the current burnup limit will allow for cycle length extensions and power uprates; in boiling water reactors (BWRs) it may allow for improved fuel utilization and reduced feed assemblies, as well as more efficient power uprates and increased capacity factors that will support the Administration’s Executive Order to facilitate 5 GW of power uprates at existing nuclear facilities. However, one of the key limitations to operating fuel to higher burnup is the risk of fuel fragmentation, relocation, and dispersal (FFRD). Recognizing the high interest in extending burnup limits, the US Nuclear Regulatory Commission (NRC) has issued Draft Regulatory Guide DG-1434, which defines an approach that would be acceptable to the NRC for addressing FFRD risk. The approach defined will require better understanding of the phenomena leading to FFRD as well as best-estimate simulation methods to understand FFRD risk in high-burnup cores. The Nuclear Energy Advanced Modeling and Simulation program is supporting the FFRD industry challenge problem through development of state-of-the-art, high-fidelity modeling and simulation LWR analysis capabilities; namely, the BISON fuel performance code and the VERA core simulator software. These tools, along with the US NRC TRACE system analysis code, have been utilized for analysis of FFRD risk in both PWR and BWR cores in recent years. The work documented in this report addresses the lack of high-fidelity research for BWRs and builds on a previous activity where the framework has been applied to Cycles 16 through 18 of Limerick Unit 1, a BWR/4, with introduction of 8 high-burnup lead use assemblies (HBLUAs) that were representative of the 8 HBLUAs loaded into Limerick Unit 2 in 2021. VERA was used in this previous activity to model rod-by-rod depletion in these cycles, and its solution was used to initialize a TRACE simulation of a large-break loss-of-coolant accident (LBLOCA) at the end of Cycle 18. In the work documented in this report, the TRACE model was improved by refining the core mesh and utilizing a new feature that allows for capturing the full 3D VERA power distribution in the model. This allows for a more detailed solution for setting BISON boundary conditions. Furthermore, the solutions from VERA and TRACE were used to set up and perform BISON simulations of about 1,000 rods sampled from the core, including all burnup levels. Utilizing two cladding burst models, it was shown that no fuel rods were predicted to burst during the postulated LBLOCA transient. Additionally, a sensitivity study was performed by artificially increasing linear heat rate during the postulated LBLOCA to identify parameters that correlate with rod burst susceptibility. Burnup, fission gas release, and hoop strain were all found to be positively correlated with rod burst susceptibility. Small-break loss-of-coolant accident (SBLOCA) analyses were also performed; these analyses predicted cladding temperature increases that were bounded by the LBLOCA cladding temperatures for all small break sizes studied for this plant. However, future refinements to the plant response assumptions during the SBLOCA could impact the predicted cladding response. Finally, a benchmark study was performed between CTF and TRACE for LOCA conditions to better qualify CTF for BWR LOCA modeling.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2021

Verification of Triso Fuel Burnup Using Machine Learning Algorithms

Pebble Bed Reactors are fueled with fuel pebbles that are circulated multiple times through the reactor vessel before discharge. During the normal operation of a PBR, ejected pebbles are returned to the reactor or discharged depending on the fuel burnup and physical condition of the pebbles. The burnup measurement is usually based on detected radiation signatures of fission products accumulated in the pebble fuel over burnup. Previous research has shown that height of photopeaks of fission products, such as 134 Cs, 137 Cs, 154 Eu, etc., can be used independently or in combination to infer or predict the level of burnup in the fuel. However, it remains challenging to measure such complex sources due to self-shielding effects, strong radiation background and intervening materials. Another operational challenge is the required high throughput of burnup measurement, which necessitates limited measurement time and thus impacts quality of measured gamma-ray spectra. Hence, advanced spectral analysis methods are needed to analyze the noisy gamma spectra and predict the burnup values. We propose to use machine learning (ML) method to interpret gamma-ray spectra and predict the burnup values of the pebbles. ML has achieved widespread success and adoption across a few domains that require pattern recognition and analysis in varied data types. In this work, we apply three proven ML approaches - multilayer perceptrons, convolutional neural networks, and transformers - to the task of predicting fuel burnup from measured gamma spectra, and compile a dataset of simulated spectra for training and validation of the ML models. In this paper, we will discuss the network architecture of these three ML approaches and compare the performance of the simplest of these (MLP) to a standard linear regression.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2022

Status of the OECD/NEA Watts Bar unit 1 benchmark and calculations of local reactor core power data of the Zero Power physics tests

The paper aims to provide an update on the status of the Organization for Economic Cooperation and Development (OECD) / the Nuclear Energy Agency (NEA) Tennessee Valley Authority (TVA) Watts Bar 1 (WB1) Multi-Physics Multi-Cycle depletion benchmark and the results associated with Exercise 1. The benchmark relies on the set of benchmark progression problems developed by the Department of Energy (DOE) Consortium for the Advanced Simulation of Light Water Reactors (CASL) for the Virtual Environment for Reactor (VERA), which are based on real plant design and operational data. The OECD/NEA TVA WB1 benchmark is designed for validation of both traditional and novel high-fidelity multi-physics codes to analyze Pressurized Water Reactors (PWR) depletion cycles. The activities are conducted under the Expert Group on Reactor Systems Multi-Physics (EGMUP) at NEA/OECD. In this work, we analyze Exercise 1 of the benchmark: stand-alone Three-Dimensional (3D) neutronics at Start-up Zero Power Physics Test (ZPPT) at Hot Zero Power Conditions (HZP) and the resulting power maps. The code used to model the exercise is the continuous energy Monte Carlo code Serpent 2.1.31 along with the nuclear data library ENDF/B-VII.1. Serpent results are compared with the high-fidelity deterministic code MPACT, which is part of VERA. The paper presents three selected results from power calculations required output. The results compared are the normalized axially integrated radial core power maps, the normalized axial averaged core power shapes, and the normalized core hottest and coldest assemblies radial power maps. The Root Mean Square Deviation (RMSD) between Serpent and MPACT is 0.51 % for the axially integrated radial core power map, 1.41 % for the axial averaged core power shape, 2.42 % for the hottest assembly axial power shape, 0.88 % for the coldest assembly axial integrated hottest assembly radial pin power map, and 0.17 % for the axially integrated coldest assembly radial pin power map. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2022

Nonnuclear Experimental Capabilities to Support Design, Development, and Demonstration of Microreactors

This work provides a summary of selected experimental capabilities being developed to support nonnuclear testing and demonstration of technology in support of microreactors under the U.S. Department of Energy’s (DOE’s) Microreactor Program. Major capabilities include the Single Primary Heat Extraction and Removal Emulator (SPHERE) and the Microreactor Agile Non-nuclear Experimental Test Bed (MAGNET). The SPHERE facility allows for controlled testing of the steady-state and transient heat rejection capabilities of a single heat pipe using electrical heaters that simulate nuclear heating. The facility is capable of monitoring axial temperature profiles along the heat pipe and surrounding test articles during startup, steady-state operation, and transients. Instrumentation includes noncontact infrared thermal imaging, surface thermocouples, spatially distributed fiber optic temperature and strain sensors, electrical power meters, and a water-cooled, gas-gap calorimeter for quantifying heat rejection from the heat pipe. The facility can be operated under both vacuum and inert-gas conditions. The MAGNET facility is a large-scale, 250-kW electrically heated microreactor test bed to enable nonnuclear experimental evaluation of a variety of microreactor concepts. It can be supplied to electrically heat a scaled section of a microreactor and further test the capabilities of heat rejection systems. The initial MAGNET experiments will support technology maturation and reduce uncertainty and risk associated with the design, operation, and deployment of monolithic heat pipe–based reactors. However, this test bed can broadly be applied to multiple microreactor concepts to evaluate a wide range of thermal-hydraulic and structural phenomena such as interface coupling with power conversion units and other collocated systems. MAGNET can evaluate integral thermomechanical effects during electrical heating of an array of heat pipes in a larger test article. Examples of initial testing will include thermal stresses in the monolith and the impact of debonding of a heat pipe from the core block and how that failure could impact surrounding heat pipes, i.e., understanding the potential for cascading failure. This work also discusses some modeling capabilities that can support experiment design, analysis, and interpretation, including the heat pipe code Sockeye and a comparison of thermal-structural simulations performed using ABAQUS and STAR-CCM+.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2023

A mechanistic model for creep and thermal aging in Alloy 709

This report describes a physics-based model for creep and thermal aging in Alloy 709. Alloy 709 is an advanced austenitic alloy, targeted for use in future Sodium Fast Reactors (SFRs) and other advanced reactors. The material has superior high temperature properties compared to currently qualified 316 and 304 stainless steels. However, the available creep and thermal aging test database for Alloy 709 is significantly more limited compared to the historical materials. The physics-based model developed here is one way to accelerate the qualification of the material by providing more accurate long-term predictions for creep properties and thermal aging, compared to current empirical time-extrapolate techniques. The crystal plasticity finite element model is used to predict the deformation and failure of alloy 709. The same setup for the CPFE model is used in both the baseline model calibration process and the simulation campaigns for parameter inference. Specific constitutive choices are made for Alloy 709 to capture the primary deformation mechanisms. The dislocation creep formulation developed by Hu and Cocks is extended to account for coupled precipitation formation and the grain boundary cavitation model developed by Sham, Needleman, et al. is used to model grain boundary cavitation-induced failure. A novel update algorithm is proposed to render the semi-discrete constitutive update for the Sham-Needleman model unconditionally stable. A progressive calibration approach is adopted based on the observations that several types of material responses can be effectively decoupled. A surrogate model is trained based on full-fledged CPFE simulations to accelerate the forward model evaluations, and stochastic variational inference (SVI) is used to calibrate the unknown microstructural model parameters. The calibrated mechanistic model is used to predict the long-term creep life of Alloy 709, and the predictions are compared against classical empirical approaches.

36 MATERIALS SCIENCE↗
DOE OSTI2025

PSA 2025 DPRA for Cyber Optimization

Cyberattacks can have many different attack paths, durations, and goals. There are also many different mitigation options involving hardware, software, and/or humans. Evaluating defense options should include quantitative evaluation of overall effectiveness to make cost and risk-informed decisions. Typical cyberattack modeling methods only provide a qualitative evaluation and have difficulty with time dependent scenarios. The main areas of cybersecurity are confidentiality, integrity, and availability. For companies with cyber-physical systems such as advanced nuclear reactors, cyber-related integrity is a requirement set by the U.S. Nuclear Regulatory Commission. But companies are also concerned about availability or reliability as a business case. As cyber threats are evolving to a business-for-hire structure, more attacks focus on disrupting business success and reliability, causing financial and economic stability risk. Companies want reliability analysis while optimizing cost, which requires more than safety modeling methods. Dynamic-state-based and Markov-based modeling provides a method for better cyber scenario modeling with timing and conditional features not found in other numerical evaluation methods. EMRALD (Event Modeling Risk Assessment using Lined Diagrams) is a dynamic risk analysis modeling and simulation tool and has features that reduce modeling issues such as state-base explosion found in Markov-based tools. It has been used to model different time-dependent events including plant behavior and operator procedures. As a general modeling tool, EMRALD can also be used to model cyberattack scenarios with varying mitigation options and quantify effectiveness, producing numerical data for risk-informed decisions. This paper uses EMRALD to demonstrate that dynamic risk analysis can be used for cyber threat modeling to provide insights for design decision-making and optimize defense strategies.

97 - MATHEMATICS AND COMPUTING↗
DOE OSTI2020

The MPACT 2020 Milestone: Safeguards and Security by Design of Future Nuclear Fuel Cycle Facilities.

The Materials Protection, Accounting, and Control Technologies (MPACT) campaign, within the U.S. Department of Energy Office of Nuclear Energy, has developed a Virtual Facility Distributed Test Bed for safeguards and security design for future nuclear fuel cycle facilities. The purpose of the Virtual Test Bed is to bring together experimental and modeling capabilities across the U.S. national laboratory and university complex to provide a one-stop-shop for advanced Safeguards and Security by Design (SSBD). Experimental testing alone of safeguards and security technologies would be cost prohibitive, but testbeds and laboratory processing facilities with safeguards measurement opportunities, coupled with modeling and simulation, provide the ability to generate modern, efficient safeguards and security systems for new facilities. This Virtual Test Bed concept has been demonstrated using a generic electrochemical reprocessing facility as an example, but the concept can be extended to other facilities. While much of the recent work in the MPACT program has focused on electrochemical safeguards and security technologies, the laboratory capabilities have been applied to other facilities in the past (including aqueous reprocessing, fuel fabrication, and molten salt reactors as examples). This paper provides an overview of the Virtual Test Bed concept, a description of the design process, and a baseline safeguards and security design for the example facility. Parallel papers in this issue go into more detail on the various technologies, experimental testing, modeling capabilities, and performance testing.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2022

Development of a high fidelity model of the CROCUS experimental reactor

Measurements of scalar flux distributions with fine spatial and energy resolutions are needed to remedy one of the validation shortcomings of the novel neutronics full core solvers, such as MPACT and nTRACER. While a very detailed resolution of the flux can be calculated with such codes, only a limited experimental data set is available to check their accuracy. Such type of measurements are on-going at the zero power reactor CROCUS, operated at the Laboratory for Reactor Physics and System Behaviours of the EPFL, thanks to the development of advanced miniature neutron detection systems. This kind of experimental data would provide the community with a suitable benchmark for the validation of high fidelity neutronics solvers. In parallel, a multi-physics solver for steady-state and transient analysis of nuclear reactors, named GeN-Foam, has been developed. Based on the finite-volume OpenFOAM library, GeN-Foam provides us with enough flexibility to analyze non-conventional reactor geometries such as that of CROCUS. While CROCUS heterogeneities cannot be modeled by MPACT and nTRACER for the moment, GeN-Foam offers a unique opportunity to build a high fidelity model which mimics these codes' method to reach sub-pin simulation resolution. This document aims at describing the work achieved to get from the existing GeN-Foam model of the CROCUS reactor based on a structured mesh and using the neutron diffusion, the first high-fidelity model using discrete ordinates method as an approximation to neutron transport and an unstructured mesh for inter lattice water gap description and sub-pin heterogeneous modeling. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2022

Summary of Development for Structural Component Modeling in Fiscal Year 2022

This report summarizes efforts performed during Fiscal Year 2022 to develop capabilities for modeling structural component degradation in support of the U.S. Department of Energy's Nuclear Energy Advanced Modeling and Simulation Program. These efforts were centered around development of capabilities for the Grizzly code. Efforts focused both on foundational engineering-scale analysis capabilities for damage and shell formulations and on material-scale tools for accounting for irradiation effects in Grade 91 steel. A major outcome of this effort was the development of a general-purpose tool for nonlocal averaging of material properties, which enabled nonlocal damage models. In addition, the applicability of the shell elements in MOOSE has been expanded to allow modeling a wider range of component geometries and using a wide variety of material models. For irradiation effects on materials, a previously developed cluster dynamics model for light water reactor pressure vessel steels has been adapted for application to Grade 91 alloy. This work builds on prior efforts to build a flexible, capable code for addressing a variety of aging and component performance issues in nuclear power plant structural components.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Atomistic Investigation of Plastic Deformation and Dislocation Motion in Uranium Mononitride

Uranium mononitride (UN) is a promising advanced nuclear fuel due to its high thermal conductivity and high fissile density. However, many aspects of its mechanical behavior, particularly at reactor-relevant conditions, remain unclear. In this study, molecular dynamics (MD) simulations were employed to investigate the deformation behavior and dislocation motion in UN. We found that the Kocevski potential predicts the principal slip system as $\frac{1}{2}$ $\langle110\rangle${110}, aligning with experimental data. On the other hand, the Tseplyaev potential predicts slip to primarily occur on $\frac{1}{2}$ $\langle110\rangle${111}. MD simulations of stress–strain behavior were used to estimate the nanoindentation hardness, revealing that the Kocevski potential accurately predicts hardness even though it fails to model dynamic plasticity. Complete dislocation mobility functions have been fitted for the edge and screw dislocations in both the thermally activated and phonon-drag regimes. The 300 K linear mobility of the edge dislocation using the Tseplyaev potential was found to be 817 Pa -1 ·s -1 , whereas that of the screw dislocation using the Kocevski potential was found to be 4546 Pa -1 ·s -1 . At intermediate stresses, we observed that the subsonic steady-state motion of the edge dislocation in UN is intermittently interrupted by velocity jumps, reaching the average sound velocity. Finally, the threshold Schmid stress is calculated as 179–197 MPa, which gives an upper-limit estimate of the uniaxial yield stress of polycrystalline UN of 548–603 MPa. These findings, including the fitted dislocation mobility function, provide essential input for future plasticity and dislocation dynamics models of nuclear fuels.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Irradiation enhanced diffusion and diffusional creep in U₃Si₂

U₃Si₂ is a candidate as an advanced fuel for light water reactors (LWRs). Compared to UO₂, there are significant data gaps for the thermophysical and thermomechanical properties of U₃Si₂. Atomic scale simulations can help fill in those gaps, while also providing a more mechanistic understanding of the material properties. Creep is an important property for fuel performance as it influences the pellet-cladding gap, which in turn affects the temperature of the fuel (a key parameter in many other aspects of fuel behavior). In this work, we employed a DFT-informed cluster dynamics framework to predict point defect concentrations in U₃Si₂. The concentrations, diffusivities, and volumes of these defects were used to develop a diffusional creep model based on bulk (Nabarro-Herring) and grain boundary (Coble) diffusion processes. It was found that irradiation enhanced Nabarro-Herring creep is dominant at low temperatures, while Coble creep dominates for high temperatures. The model compares well against available experimental data and has been implemented in BISON. A demonstration case using simple power profiles has been carried out, showing that negligible creep occurs due to the low temperatures experienced by U₃Si₂, a consequence of its high thermal conductivity.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2020

Modular high temperature gas reactor core modeling with RELAP5-3D/PHISICS – Optimization schemes for load following

The objective of this study is to develop a 3D/NK model to study the load following operation of a Modular High-Temperature Gas-Cooled Reactor (MHTGR). The selected design is the 350 MW prismatic, graphite moderated, helium cooled thermal reactor based on the MHTGR-350 transient benchmark led by the High-Temperature Gas-Cooled Reactor (HTGR) Methods Core Simulation Group at Idaho National Laboratory (INL) in the framework of the Organization for Economic Cooperation and Development Nuclear Energy Agency (OECD/NEA). This kind of reactor usually reacts very slowly to the perturbation of the core parameters due to the large amount of graphite in the core. This kind of behavior promotes the reactor stability but on the other hand limits the reactor load-following operability. Recently advances in gas reactor designs have made load-following in gas reactors a feasible and achievable goal. Modern nuclear reactors (such as the MHTGR-350) are designed to withstand the structural stresses associated with load-following. Operating the reactor in load-following mode will inevitably reduce the load factor. Although a higher load factor means more revenue and the best usage of the fuel, following the variable energy demand will increase the maximum achievable fraction of generated nuclear power, being no more limited to the base load power generation. In general, if low impact on material aging and the safe operability are demonstrated the plant economics will be minimally affected. In order to ensure that the system can be safely operated in a load-following mode an extensively study has been carried out. Some tests with linear coolant mass flow rate change demonstrated that the reactor behavior is suitable for operation in load following mode. This assumption has been confirmed by a 4 days load following transient test in which the reactor supplied the requested power with a negligible error.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2026

Rapid Gamma Simulations of TRISO Fuel Elements

As energy demand rises, nuclear energy, particularly from reactors that use tristructural isotropic (TRISO) fuels, has gained attention due to the fuel’s enhanced resistance to radiation damage and high temperatures. This report investigates the modeling capabilities of the Gamma Detector Response and Analysis Software (GADRAS) for TRISO fuels, focusing on the gamma signatures of TRISO particles, which have not been extensively explored. Using the Monte Carlo N-Particle (MCNP) code as a benchmark, we developed both homogeneous and heterogeneous models of TRISO pebbles to analyze gamma spectra. Our findings reveal that the homogeneous and heterogeneous models produced different gamma signatures. Additionally, the GADRAS heterogeneous model significantly reduces computation times compared to MCNP, enabling effective modeling of gamma signatures for safeguards applications. This advancement is essential for the International Atomic Energy Agency (IAEA) in detecting anomalies and potential smuggling attempts in TRISO reactor fuel elements.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗