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At least 379 records · Page 21

Status of Modifications to the AGR-3/4 Fission Product Transport Model

A one-dimensional (1D) finite-element model of the AGR 3/4 experiment fission product distributions based on the Multiphysics Object-Oriented Simulation Environment (MOOSE) framework has been revised and implemented within BISON, with improvements which allow for detailed temperature histories to be used for analyses. Empirically determined concentration profiles and ring inventories from the AGR-3/4 experiment have been compiled for comparison purposes. Ongoing efforts to build fission product diffusion models which can describe the applicable physics for isotopic concentration profiles in each AGR-3/4 capsule are discussed, as well as the suitability of each isotopic concentration profile in each capsule for obtaining transport parameters.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Results of the Micromorphic Upscaling Workflow for the PSAAP III Year 3 Report

Predicting the mechanical response and failure of heterogeneous materials has proven difficult. Multiscale numerical methods based in higher order continuum theories attempt to bridge the gap between microscale and macroscale structural behavior. Micromorphic continuum theories have shown promise. The Tardigrade software package is an implementation of Eringen’s micromorphic continuum theory with capabilities to support multiscale material modeling workflows. These include homogenization through the Micromorphic Filter, calibration of micromorphic material models, and macroscale simulation in Tardigrade-MOOSE. This work discusses micromorphic upscaling efforts of the University of Colorado Boulder PSAAP III multidisciplinary simulation center (MSC). Verification studies are presented that compare the accuracy of the upscaling workflow with analytical solutions for a trivial stress state and homogeneous material using direct numerical simulations (DNS) conducted in the Ratel finite element method (FEM) and GEOS material point method (MPM) codes. These verification studies consider upscaling using the Micromorphic Filter for a “single filter domain”. Finally, DNS of a heterogeneous composite material is upscaled using a “multiple filter domain” method.

36 MATERIALS SCIENCE↗

SAM Software Quality Assurance Plan Implementation and NQA-1 Assessment

The System Analysis Module (SAM) is an advanced and modern system analysis tool being developed at Argonne National Laboratory under the U.S. DOE Office of Nuclear Energy’s Nuclear Energy Advanced Modeling and Simulation (NEAMS) program. As a modern-day software, SAM development included efforts to follow best practices in software development. These best practices include version control using git, independent reviews of development activities, and detailed descriptions of developments and bug fixes using the GitLab issue and merge request system. In Fiscal Year 2023 (FY23), the SAM development team set out to formalize a Software Quality Assurance (SQA) program that allowed industry partners to credit the informal steps being taken by the SAM development team to ensure the quality of the software. As part of formalizing an SQA program, a SQA Plan (SQAP) was developed, implemented, and assessed. The SAM SQAP targets compliance with NQA-1-2008/2009 Addenda. The SQAP builds on the MOOSE SQAP and the Argonne SSQAPP while accounting for the needs of the multi-organization SAM development team. Modifications to the SAM repository structure, including a new testing system, updated test cases, and the development of an internal website, facilitate the implementation of the SAM SQAP. The initial assessment of the SAM SQAP indicated that the SAM SQAP was adequately and effectively implemented and additional work was required to improve the compliance of the SAM SQAP with NQA-1 2008/2009 Addenda. Several improvements to the SQAP have already been drafted to address these assessments and future work is planned to further improve the SAM SQAP in support of end-user needs.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Coupled SAM/Griffin Model of a Reference Pebble Bed High-Temperature Gas Cooled Reactor for Multi-Physics Simulations

An effort has been dedicated to developing a reference model for multi-physics coupled simulation of the pebble bed high-temperature gas-cooled reactor (PB-HTGR) with SAM and Griffin computer codes for safety analysis and licensing purpose. The reference problem of a prototypical reactor design serves as the foundation for the U.S. NRC (Nuclear Regulatory Commission) to verify the adequacy of computer codes and evaluation models for specific reactor types. In this work, a SAM model of the HTR-PM reactor has been developed based on publicly available design information and the multi-dimensional Pronghorn model developed by Idaho National Laboratory. The SAM HTR-PM model includes a multi-dimensional core region and 0- D/1-D fluid components. Additionally, a simplified air RCCS loop is modeled for decay heat removal. The Griffin model is based on a recent work by Idaho National Laboratory. The coupling between the models is achieved through the MOOSE MultiApp system. Both steady-state and transient scenarios were simulated to demonstrate the coupled model’s capability for multi-physics simulations.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

BISON Fuel Fragmentation Relocation and Dispersal (FFRD) Assessment Database for Eventual Use in Bayesian Calibration

Existing light-water reactor (LWR) fuel vendors have been interested in seeking increased discharge burnups of nuclear fuel rods for improved economics for quite a few years. With increased burnups come additional challenges that must be addressed. It has been experimentally observed that average burnups higher than the current regulatory limit of 62 MWd/kgU may undergo fuel fragmentation, relocation, and dispersal (FFRD) during a loss-of-coolant accident (LOCA). Industry must demonstrate approaches to mitigate FFRD. In an effort to support industry, the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program within the U.S. Department of Energy (DOE) has for several years invested in developing multiscale models and creating a validation/assessment database for these models to study the mechanisms driving FFRD. This report provides an update on changes made to the assessment database and new models added to BISON to support the study of fuel rod behavior during FFRD. An effort has been initiated this year to begin adding dedicated inputs to the publicly available Virtual Test Bed (VTB) repository for industry use. A section of this report details the efforts made in this area. NEAMS has recently developed new capabilities in the Multiphysics Object-Oriented Simulation Environment (MOOSE) framework’s stochastic tools module for calibration using Bayesian inference. The goal in the future is to use these capabilities to calibrate and identify weaknesses in the existing BISON models for FFRD. The report concludes with a discussion on the models most likely to benefit the most from such calibration.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Improved Fast Reactor Capability of Griffin in FY23

Griffin is a MOOSE based reactor multiphysics analysis application jointly developed by Idaho National Laboratory and Argonne National Laboratory under the DOE-NE NEAMS program. In FY23, we enhanced capabilities required for fast reactor analysis. This effort included primarily updating the cross-section generation workflow using MC2-3 for various reactor configurations, such as homogeneous, duct-heterogeneous, ring-heterogeneous, and fully-heterogeneous geometries. In addition, we initiated the implementation of a multi-cycle depletion and shuffling capability. To support fast reactor simulation capabilities, we significantly improved the performance of the DFEM-SN-based R-Z transport solver to efficiently solve ultrafine group (over 1000 groups) transport problems. Additionally, the performance of HFEM-PN was improved by introducing red-black iteration, the cmfd acceleration technique, and various optimizations. We also completed the pin power reconstruction capability to support multiphysics simulations while identifying and addressing issues associated with SPH equivalence parameter approach. These enhanced capabilities for fast reactor core simulations, specially HFEM-PN and pin power reconstruction features, were applied to benchmark problems involving ABTR and ABR-1000. These applications showcased excellent agreement with Monte Carlo and other code solutions in terms of eigenvalue, control rod worth, and assembly and pin powers.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Coupling of Spark Plasma Sintering with Advanced Modeling to Enable Process Scale-Up: Presentation to DOE-NE [Slides]

The research goal of this project is to develop at Idaho National Laboratory (INL) a first-of-its-kind Multiphysics Object-Oriented Simulation Environment (MOOSE)-based, multiscale, multiphysics spark plasma sintering (SPS) modeling and simulation code application, termed “Freya.” Freya will simulate the thermo-mechanical-electrical aspects of the SPS fabrication process and will be paired with lower length scale sub-models, such as phase-field, to predict the resulting microstructure. SPS is an advanced manufacturing process that can be used to solve a variety of material manufacturing challenges; however, this process is an extremely challenging problem for modeling and simulation. The SPS process is inherently multiphysics and multi-scale, with the macroscale electro-thermo-mechanical behavior linked intricately to the microstructure evolution of the part being sintered. Accurate modeling and simulation tools, specifically geared towards the SPS process, are needed to predict the influence of the multiple variables involved in the manufacturing process. Modeling and simulation accuracy is achieved and demonstrated through comparison to multiple validation experiments. The validation efforts for Freya include both separate effects and complete multiphysics SPS process experiments. One of the key benefits this Laboratory Directed Research & Development (LDRD) project offers stems from the emphasis placed on experimental validation of the Freya models, both on the individual length scales and of the final coupled multiscale multiphysics simulations. Experimental validation of Freya’s multiscale coupling capability provides the technical credibility necessary for potential future industry and research partners to accept the simulation predictions.

36 MATERIALS SCIENCE↗

BISON: A Flexible Code for Advanced Simulation of the Performance of Multiple Nuclear Fuel Forms [Slides]

As fuel vendors and designers pursue the development of advanced reactors or the increase in burnup limits for existing reactors, advanced computational tools are necessary to understand the fuel performance. BISON, a fuel performance code developed primarily at Idaho National Laboratory, which is built upon the Multiphysics Object-Oriented Simulation Environment (MOOSE), provides capabilities to analyze multiple nuclear fuel forms in a wide variety of dimensions. Since its inception, BISON has been used to investigate the performance of light-water reactor fuel rods, accident tolerant fuel concepts, metallic and mixed-oxide (MOX) fuels for fast reactors, plate fuels for research reactors, and tri-structural isotropic (TRISO) fuel particles. This talk will provide a history of BISON, highlights of major development milestones, tributes to key contributors, and applications of its use to various fuel forms in one-, two-, and three-dimensions.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Initial Demonstration of New Griffin Technologies for Simulating the Running-In Phase of Pebble Bed Reactors

Griffin is a reactor multiphysics modeling application based on MOOSE (Multiphysics Object-Oriented Simulation Environment) and specifically targeting transient modeling of advanced reactors. Griffin has been used recently to model pebble-bed reactors for the Nuclear Regulatory Commission (NRC) Office of Nuclear Regulatory Research and the Advanced Reactor Technology program. This modeling work has focused thus far on the direct calculation of equilibrium cores. This report documents an initial demonstration of a new running-in simulation capability. The new running-in capability is verified using the existing direct equilibrium core calculation capability. A simplified pebble-bed reactor model is then used to demonstrate the running-in simulation capability. This demonstration shows that Griffin is able to simulate years of operation during the running-in phase efficiently with each depletion step taking only several seconds. Two new technologies are also presented in this report which have been developed in Griffin that will be essential for improved accuracy both of the direct equilibrium core computation and the new running-in simulation capability. The first technology is an online cross section generation capability specifically targeted for pebble-bed reactors. This will improve the accuracy of the depletion calculation as the cross sections are generated at the exact core status. This also avoids the difficult step of pre-generating a separate standalone multigroup cross section set. Secondly, a newly implemented discretization for discontinuous finite element method (DFEM) SN transport in cylindrical (RZ) coordinates, which can be solved efficiently using the existing SN sweep solver, is discussed and some results are shown demonstrating the usefulness of the additional accuracy transport provides over a diffusion approximation.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Bayesian Analysis of TRISO Fuel: Quantifying Model Inadequacy, Incorporating Lower-Length-Scale Effects, and Developing Parallel Active Learning Capabilities

The U.S. Department of Energy (DOE)’s Nuclear Energy Advanced Modeling and Simulation (NEAMS) program aims to develop predictive capabilities by applying computational methods to the analysis and design of advanced reactor and fuel-cycle systems. This program has been providing engineering-scale support for the continued development of BISON, a high-fidelity, high-resolution fuel performance tool. Fuel behavior in nuclear reactors is governed by a complex network of mechanisms that interact with various other physics aspects in the reactor system. Any model developed to represent fuel behavior will likely be idealized, resulting in uncertainties when comparing their predictions against the observed data. In Fiscal Year (FY)-23, we initiated the Uncertainty Quantification (UQ) work by using Bayesian methods to establish a level of model trustworthiness and further improve it, with a particular emphasis on TRI-Structural isOtropic (TRISO) nuclear fuel. This year, we further expanded on that UQ work by investigating an approach to quantifying model inadequacy and accounting for lower-length scale (LLS) effects in TRISO silver (Ag) release modeling. Furthermore, we are implementing parallel active learning capabilities to reduce the computational cost (i.e., required computational resources and elapsed time) of performing UQ. Specifically, we utilized The Kennedy O’Hagan framework for Bayesian uncertainty quantification (KOH) to account for model inadequacy in TRISO Ag release predictions made by BISON. The KOH framework represents an improvement over the standard Bayesian framework used in FY-23. Explicitly accounting for model inadequacy in the Bayesian framework helps establish the level of experimental noise uncertainty in the Advanced Gas Reactor (AGR) data. We compared the inverse UQ results obtained from both the standard Bayesian and KOH frameworks in light of the AGR-2/3/4 data, and also compared the predictive UQ results obtained from these two frameworks in light of the AGR-1 data. Next, we investigated the impact of considering LLS effects in the Ag release simulations. We developed an expanded database of LLS simulated effective diffusivities for Ag, covering a wide range of microstructures and temperatures. Using this database, we developed a framework for incorporating LLS effects into the engineering-scale Ag release UQ. We developed both parametric and non-parametric approaches for bridging the length scales. We then investigated the inverse UQ results in light of the AGR-2/3/4 data and the predictive UQ results in light of the AGR-1 data, and compared the LLS-informed approach and the Arrhenius equation, which does not include microstructure information. Finally, we discussed implementing parallel active learning capabilities in the Multiphysics Object Oriented Simulation Environment (MOOSE)/BISON to reduce the computational cost (i.e., computational resources and elapsed time) of Bayesian UQ. For verification purposes, we first tested these new capabil ities on a species interaction problem. We then demonstrated them on the TRISO Ag release application, showing that parallel active learning capabilities can enhance the accuracy of UQ while also substantially reducing the computational cost in comparison to the reference methods developed in FY-23.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Assessment and validation of NEAMS tools for high-fidelity multiphysics transient modeling of microreactors: Application of NEAMS codes to perform multiphysics modeling analyses of micro-reactor concepts

The NEAMS Multiphysics Applications team aims at providing assessment of code useability and functionality for microreactor design and analyses, together with demonstration of their capabilities to properly capture the steady-state and time-dependent behavior of different microreactor concepts. In FY-24, significant progress was achieved in improving multi-physics models of several microreactors systems: HP-MR, GC-MR and KRUSTY. These efforts focused on solving more complex multiphysics problems enabled by enhanced tools capability, verifying and validating results obtained, providing feedback to developers for suggested improvements, and sharing these models to facilitate user training. A series of new multiphysics transients were completed on the HP-MR (using Griffin/BISON/Sockeye) with core startup transient, control drum inadvertent rotation accident, and hydrogen leakage from hydride moderator (also including SWIFT). On the GC-MR, a new full-core model was developed and analyzed through a series of new multiphysics (Griffin/BISON/SAM) transients to simulate moderator leakage (also including SWIFT), flow blockage and coolant depressurization. Additional and updated TRISO failure analyses were completed on the HP-MR unit-cell and GC-MR assembly models leveraging improved TRISO modeling capabilities. The amount of SiC failure following accidental transients at end-of-life was null. However, GC-MR assembly TRISO analysis highlighted Pd penetration rate can be problematic and may require design changes on the studied microreactor concept. The neutronics discrepancies observed on the KRUSTY model in previous years were resolved using hybrid set of Monte Carlo/Deterministic cross-sections. The multiphysics (Griffin neutronics / BISON thermal-mechanics) 15₵ insertion transient simulation displayed good agreement when comparing with experimental data. Initial modeling of the 30 ₵ reactivity insertion also displays promising results. Such close agreement provides important validation data that can be leveraged by the NEAMS program and by microreactor vendors to support licensing of their technology. Finally, important experience was gathered with the NEAMS tools leading to several user feedback shared with tools developers, especially with regards to MOOSE mesh generator and Griffin. This project led to many publications demonstrating modeling capabilities, and to three models shared on the Virtual Test Bed.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

SAM Theory Manual

The System Analysis Module (SAM) is an advanced and modern system analysis tool under development at Argonne National Laboratory for advanced non-LWR reactor safety analysis. It aims to provide fast-running, modest-fidelity, whole-plant transient analyses capabilities, which are essential for fast turnaround design scoping and engineering analyses of advanced reactor concepts. While SAM is being developed as a system-level modeling and simulation tool, advanced modeling techniques being implemented include a reduced-order three-dimensional module, pseudo 3-D conjugate heat transfer modeling in reactor core, flexible and multi-scale modeling of heat transfer between fluid and structures, in addition to the advances in software environments and design, and numerical methods. SAM aims to be a generic system-level safety analysis tool for advanced non-LWRs, including Liquid-Metal-cooled fast Reactors (LMR), Molten Salt Reactors (MSR), Fluoride-salt-cooled High-temperature Reactors (FHR), and High-Temperature Gas-cooled Reactors (HTGR). SAM takes advantage of advances in physical modeling, numerical methods, and software engineering to enhance its user experience and usability. It utilizes an object-oriented computational framework (MOOSE), and its underlying meshing and finite-element library and linear and non-linear solvers, to leverage the modern advanced software environments and numerical methods. This document provides the theoretical and technical basis of the code to help users understand the underlying physical models (such as governing equations, closure models, and component models), system modeling approaches, numerical discretization and solution methods, and the overall capabilities in SAM. As new code capabilities and features are added, the SAM Theory Manual will be updated periodically to keep it consistent with the state of the development.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

SAM User's Guide

The System Analysis Module (SAM) is a modern system analysis tool being developed at Argonne National Laboratory for advanced non-LWR safety analysis. It aims to provide fast-running, whole-plant transient analyses capability with improved-fidelity for Sodium-cooled Fast Reactors (SFR), Lead-cooled Fast Reactors (LFR), and Molten Salt Reactors (MSR) or Fluoride-cooled High-temperature Reactors (FHR). SAM takes advantage of advances in physical modeling, numerical methods, and software engineering to enhance its user experience and usability. It utilizes an object-oriented application framework (MOOSE), and its underlying meshing and finite-element library (libMesh) and linear and non-linear solvers (PETSc), to leverage the modern advanced software environments and numerical methods. This document provides a user’s guide, which will help users understand the input description and core capabilities of the SAM code. A brief overview of the code is presented, as well as how to obtain and run it. The input syntax for various parts of the code is provided. Additionally, a number of example problems, starting with simple unit component problems to problems with increasing complexity, are provided. Because the code is still under active development, this SAM User’s Guide will evolve with periodic updates.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Improved Weld Residual Stress Modeling System in BlackBear

This report presents enhancements to the MOOSE-based BlackBear application aimed at improving its capability to simulate welding and other thermo-mechanical manufacturing processes. Two primary avenues of improvement are pursued. First, to enhance user accessibility, we introduce a centralized default block restriction mechanism that ensures coverage checks are performed within user-specified default blocks. This default setting is applied consistently to all block-describable objects, such as variables, kernels, and more. In addition, we develop a modular action for moving heat source simulations, which integrates path file parsing, subdomain modification, and heat source kernel enforcement into a single, streamlined configuration. Second, to improve solver robustness, we implement an alternative method for assigning initial conditions to the updated active domain during the simulation, thereby enhancing convergence behavior. To validate the framework, we design and conduct several benchmark simulations, including heat conduction with progressive material addition, linear elasticity with time-dependent material deposition, and viscoplasticity model with isotropic hardening under similar conditions. Finally, we demonstrate the effectiveness of the proposed framework through large-scale thermo-mechanical welding simulations in both two and three dimensions.

42 ENGINEERING↗

Advancements in NEAMS Tool Capabilities for Multiphysics Simulation of Fast Reactor Core Bowing and Identification of Validation Test Data

Under the U.S. Department of Energy Office of Nuclear Energy Advanced Modeling and Simulation (NEAMS) Program, an integrated multiphysics approach is being developed to model the core bowing phenomena important to liquid metal-cooled fast reactors. Core bowing is an important passive safety mechanism in liquid metal-cooled fast reactors and involves Multiphysics effects including radiation transport, fluid flow, heat transfer, and mechanical response to temperature and flux gradients. This report summarizes recent progress on developing a multiphysics, MOOSE-based workflow to predict core bowing and associated reactivity feedback. Last year, thermal fluids and mechanics were coupled on a multi-assembly benchmark problem based on ABR-1000 design. This year, the reactor physics code Griffin was assessed for readiness of core bowing calculations. Preliminary integration of Griffin’s ring-heterogeneous model with thermal fluids and thermal mechanics solvers was performed. Specifically, thermal-mechanics and reactor physics were coupled for single- and multi-assembly problems, and reactor physics and subchannel methods were coupled for a single assembly model. Finally, the workflow of all three physics was preliminarily demonstrated on a single assembly model. Caveats and future development needed have been identified. To supplement the multiphysics demonstration, verification and assessment efforts of thermos-mechanical capabilities for modeling thermo-mechanical core bowing behavior were continued by analyzing IAEA Verification Problem 5 which includes radiation swelling and creep. Additionally, a small core reactor physics benchmark defined by Japan Atomic Energy Agency (JAEA) was performed to assess neutronics models for estimating reactivity feedback. Finally, Fast Flux Test Facility (FFTF) validation test data for core bowing phenomena has been identified and summarized, with a recommended path forward for validation once this capability is mature.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Validation of Numerical Tools for Calculating Reactivity Feedback in Sodium Fast Reactors Using SEFOR Experimental Data

The Southwest Experimental Fast Oxide Reactor (SEFOR) was an experimental sodium-cooled fast breeder reactor operated from 1969 to 1972 with experiments designed to measure Doppler reactivity feedback in a wide temperature range from around 350 °F to temperatures approaching the melting point of mixed oxide fuel of around 5000 °F, providing valuable data for code validations. Co-supported by the Department of Energy (DOE) Fast Reactor Program (FRP) and the DOE Nuclear Energy Advanced Modeling and Simulation (NEAMS) program, the SEFOR benchmark project focused on using the experimental data to validate numerical tools that are used in industry and academia to design and license sodium-cooled fast reactors (SFRs). By the end of FY-25, substantial progress was achieved in the SEFOR benchmark study. A variety of numerical tools commonly used for modeling SFRs were applied to develop models for SEFOR core configurations I-D, I-E, I-I, and I-J. These included Monte Carlo codes such as MCNP, Serpent, and Shift; deterministic codes such as the legacy Argonne Reactor Computation (ARC) suite and the high-fidelity NEAMS code Griffin; and the system analysis code SAS4A/SASSYS-1 (SAS). Using these models, both SEFOR zero-power experiments and power-ascending tests were successfully simulated. Comparisons were performed against experimental measurements of core criticalities, reflector worth, kinetics parameters (Λ/βeff), isothermal reactivity feedback (from 350 °F to 760 °F at zero power), and power-ascending reactivity feedback (as power increased from 0.4 MW to 17 MW). In general, these comparisons demonstrated very good agreement between numerical results and experimental data. In Fiscal Year 26 (FY-26), the SEFOR benchmark project will continue to address the modeling issues identified in FY-25. Effort will focus on the simulation of reactivity insertion transients in SEFOR core II using the ARC/SAS model. Future work will also focus on incorporating BISON into the SEFOR core modeling process to enable the first Multiphysics simulations of the isothermal tests based on the MOOSE framework.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Implementation of Perturbation Theory and Sensitivity Capabilities in Griffin

Griffin is a Multiphysics Object-Oriented Simulation Environment (MOOSE) based reactor Multiphysics analysis application, jointly developed by Argonne and Idaho National Laboratories under the DOE-NE NEAMS program. This fiscal year, capabilities for reactivity and sensitivity evaluation using perturbation methods were implemented and verified. The First Order Perturbation Method (FOPT) was employed to compute reactivity worth resulting from small perturbations in input parameters, while the Generalized Perturbation Theory (GPT) was used to evaluate sensitivities of a range of response types, including reaction rate ratio, k-eigenvalue, neutron generation time, and effective delayed neutron fraction. These perturbation methods enable users to quantify how response quantities change due to a perturbation in a input parameter without explicitly performing an additional transport simulation for each perturbed state. In particular, the GPT formulation accounts for indirect effects arising from flux changes by solving generalized inhomogeneous equations, for which a Neumann series-based iterative solution method was developed and implemented in Griffin. The implemented reactivity and sensitivity evaluation capabilities were verified using two test problems: an infinite homogeneous system and a two-dimensional hexagonal core. The results showed excellent agreement with reference solutions obtained by a direct method based on finite difference approximation as well as GPT-based results from the PERSENT code, confirming the accuracy of both reactivity and sensitivity evaluations. Additionally, preliminary uncertainty quantification (UQ) results were obtained by combining the sensitivity values computed using GPT and external covariance data, demonstrating that the implemented sensitivity results can be reliably used for uncertainty calculations. To further demonstrate the generality and practical strength of the implementation, the sensitivity evaluation capability was successfully applied to the Empire microreactor with a geometrically complex design that poses significant modeling challenges. The results confirm that Griffin enables sensitivity evaluations even for irregular and highly heterogeneous reactor configurations, thereby establishing a foundation for UQ applications in advanced reactor designs and analyses.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Improvement and Verification of Online Cross Section Generation Capability of Griffin for TRISO-fueled Reactors

Griffin, a MOOSE-based reactor multiphysics code jointly developed by Idaho National Laboratory and Argonne National Laboratory under the DOE Office of Nuclear Energy’s NEAMS program, has pursued the development of an online multigroup cross section generation capability for a few years to enable high-fidelity, problem-dependent neutronics analyses of advanced thermal reactors. Recent advancements in Griffin’s online multigroup cross section generation capability have significantly improved the accuracy, robustness, and efficiency of self-shielding calculations for both prismatic and pebble-bed TRISO-fueled reactor applications. Key developments include a unified fuel self-shielding method applicable to both TRISO and annular compact/spherical shell fuel zone geometries; an advanced Dancoff Category-based Equivalence Theory using a bell function for non-fuel resonance treatment, achieving more than an order-of-magnitude speedup compared to the Tone method; an on-the-fly multigroup equivalence approach to mitigate group condensation errors; and a streaming correction method for pebble-bed homogenization. A proof-of-concept demonstration of on-the-fly group condensation with consistent P0 transport correction was also achieved. The method reproduced direct fine-group solutions with excellent accuracy (eigenvalue errors within 10 pcm and pin-power differences within 0.5%), but due to performance limitations of the current fixed-source solver, improvements to solver efficiency will be addressed in future work. Verification tests were performed on graphite-moderated TRISO-fueled two-dimensional core benchmark problems representing gas-cooled microreactors, heat pipe-cooled microreactors, gas-cooled pebble-bed reactors, and fluoride salt-cooled high-temperature reactors. Across all cases, Griffin showed excellent agreement with Serpent2 continuous energy Monte Carlo solutions: eigenvalue errors within 200 pcm, pin-power root-mean-square errors within 2%, and control rod and drum worth errors less than 2%. It should be noted that, for the benchmark problem, cross section generation contributed less than 3% of the total simulation times. These results demonstrate that Griffin’s online cross section generation capability delivers accurate and efficient reactor physics solutions across a wide spectrum of TRISO-fueled advanced reactor designs. With further improvements to the fine-group fixed-source solver and planned extensions to depletion, transients, and coupled neutron–gamma transport, Griffin will be well-positioned to become a powerful and comprehensive tool for advanced reactor analysis.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗