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At least 235 records · Page 13

Recent Improvements in Pronghorn for Advanced Reactor Modeling

Pronghorn is a thermal-hydraulics computational tool developed using the Idaho National Laboratory's Multiphysics Object-Oriented Simulation Environment (MOOSE). It is designed to support Computational Fluid Dynamics (CFD) modeling, ranging from subchannel and porous media analysis to Reynolds Averaged Navier-Stokes (RANS) turbulence modeling. As an integral part of the MOOSE-based suite of tools, Pronghorn seamlessly couples with other MOOSE-based applications to simulate a variety of physical phenomena. This article highlights recent significant enhancements to Pronghorn's CFD modeling capabilities and demonstrates their application to advanced nuclear reactor designs. The recent improvements in Pronghorn primarily focus on modifications to its turbulence modeling capabilities, near-wall corrections and numerical schemes. In terms of turbulence modeling, the two-equation $k-\epsilon$ and $k-\omega$ SST models have been implemented and validated with both equilibrium and non-equilibrium wall treatments. Additionally, corrections for wall roughness, and curvature, and wall-channeling in pebble beds have been introduced in the near-wall modeling. These developments enable more accurate simulations of advanced nuclear reactors. Two case studies are presented in this work: a pool-type Molten Chloride Reactor and a salt-cooled Pebble-Bed High Temperature Reactor. In both cases, the previous models in Pronghorn are compared with the new implementations, demonstrating the improved accuracy achieved with the updated models.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗

High-Burnup LOCA Burst Susceptibility BISON Analysis in PWRs and BWRs

Accurately assessing high-burnup fuel behavior during loss-of-coolant accidents (LOCAs) is essential for understanding fuel fragmentation, relocation, and dispersal (FFRD) risks across the US light-water reactor fleet. This work updates previous Nuclear Energy Advanced Modeling and Simulation (NEAMS) Program multiphysics LOCA analyses for a pressurized water reactor (PWR) and a boiling water reactor (BWR) by incorporating recent model and material property advancements in the BISON fuel performance code, including a high-burnup structure (HBS) model, revised cladding burst criteria, and updated thermal–mechanical correlations. This update was needed to support ongoing industry initiatives and upcoming regulatory changes. Full-core, rod-resolved operating histories generated using Virtual Environment for Reactor Analysis (VERA) and system-level LOCA conditions obtained from TRACE were applied to statistically representative rod samples in BISON to evaluate burst behavior and FFRD susceptibility. These calculations used two cladding burst correlations and three fuel pulverization models so that the predictions of these models could be compared. The updated PWR simulations show markedly improved numerical stability as the number of crashed simulations decreased by 95% compared to the previous study, and hence higher confidence in results. The updated PWR simulations predicted cladding bursts exclusively among once-burned, high-power rods, with two different cladding burst models identifying the same burst-susceptible population. Resulting FFRD susceptibility estimates are significantly reduced compared with earlier studies, driven by cooler predicted fuel and plenum temperatures, lower hoop strains, and reduced fission gas release in the updated models. In contrast, none of the BWR rods were predicted to burst under either burst criterion, reaffirming minimal BWR FFRD susceptibility even with updated HBS and material models. Comparisons between the PWR and BWR end-of-cycle predictions are made. Comparison with prior work highlights significant shifts in PWR fuel performance metrics and confirmation of earlier BWR conclusions. Overall, the updated results underscore the importance of having high-resolution detailed modeling capability and continuously integrating evolving material models and physics into high-resolution multiphysics simulations. The unified assessment presented here strengthens confidence in predicting high-burnup LOCA behavior by improving agreement between different cladding burst correlations. These results also provide an improved foundation for future BISON model development, FFRD susceptibility calculations.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Analysis of the High Temperature Engineering Test Reactor Using MOOSE Tools

This presentation shows the development of neutronics and thermal hydraulics models of the High Temperature Engineering Test Reactor using codes in the Multiphysics Object Oriented Simulation Environment. We show preliminary results of full-power steady state and a loss of forced cooling transient from that steady state.

21 - SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLAN↗

Assembling Multiphysics Nuclear Reactor Simulations Using the MOOSE Framework

The Multiphysics Object Oriented Simulation Environment (MOOSE) [1] is an open-source, parallel finite element framework which provides the foundation for many advanced modeling and simulation tools developed under the Department of Energy (DOE) Nuclear Energy Advanced Modeling and Simulation (NEAMS) Program [2] for the analysis of advanced reactors. The MOOSE framework provides the common foundational capability on which many NEAMS codes for reactor analysis are built. The MOOSE framework also includes several systems to assemble unique workflows and couplingamong MOOSE-based applications. In particular, the MultiApp and Transfer Systems are widely used to assemble different MOOSE-based or MOOSE-wrapped physics applications together to perform loosely or tightly coupled multiphysics simulations. The National Reactor Innovation Center (NRIC) Virtual Test Bed (VTB) [3] hosts publicly available nuclear reactor multiphysics simulation examples which leverage MOOSE’s MultiApp System to meet the modeling needs of different reactor types. The flexibility and robustness of coupling provided by MOOSE permits rapid development of coupled physics models for a wide range of reactor types and events

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Multiphysics Demonstration of Temperature-Driven Assembly Bowing in SFRs using MOOSE-Based Codes

Core bowing is an important passive safety mechanism in liquid metal cooled fast reactors. When the core restraint system is properly designed, temperature and flux gradients influence assemblies in the core to bow into less reactive configurations during accident scenarios, resulting in negative reactivity feedback. Prediction of core bowing involves complex interplay of radiation transport, impacts of fluid flow and heat transfer on duct temperature, and mechanical responses to the induced temperature and flux gradients. Under the U.S. Department of Energy Office of Nuclear Energy’s Advanced Modeling and Simulation (NEAMS) Program [1], an integrated multiphysics approach is being developed to model the core bowing phenomena in liquid metal-cooled fast reactors with the Multiphysics Object Oriented Simulation Environment (MOOSE) [2]. In this methodology, the MOOSE-based reactor physics code Griffin [3] will solve the neutron transport equation and determine the power distribution. With the detailed power distribution from Griffin, the subchannel analysis codes MOOSE-Subchannel [4] and Pronghorn [5] are utilized to calculate the assembly temperature distribution. MOOSE’s Solid Mechanics [6] and Contact [7] Modules are leveraged to calculate the thermal expansion and duct bowing displacement with the duct wall temperature from thermal hydraulics calculation. In this work, an initial one-way coupling demonstration of the integrated multiphysics approach has been performed on a seven-assembly problem based on the sodium-cooled fast reactor ABR-1000 design [8]. The neutronics calculation with Griffin is not yet involved in the current simulation. MOOSE-Subchannel and Pronghorn evaluate fluid and solid temperature based on a fixed power distribution. In addition, one-way coupling is utilized in this coupled calculation, via Pronghorn passing the duct temperature data to the MOOSE Solid Mechanics calculation. An assessment of the Solid Mechanics module was performed in parallel to verify duct bowing behavior with duct-to-duct contact phenomenon [9]. The displacement from MOOSE Solid Mechanics is not yet transferred back and utilized in the Pronghorn and MOOSE-Subchannel calculation. This model will be available on the National Reactor Innovation Center (NRIC) Virtual Test Bed (VTB) repository [10]. Future stages of this work will involve solving problems of increasing complexity as well as adding more physics (e.g. reactor physics) to the integrated workflow to reach the end goal of modeling the core bowing phenomenon with an integrated multiphysics workflow.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗

ANS MultiApps tutorial

The Multiphysics Object-Oriented Simulation Environment (MOOSE) [1] is an open-source, parallel finite element framework which provides the foundation formany advanced modeling and simulation tools developed under the Department of Energy’s (DOE’s) Nuclear Energy Advanced Modeling and Simulation (NEAMS) program [2] for the analysis of advanced reactors. The MOOSE framework provides the common foundational capability on which many NEAMS codes for reactor analysis are built. The MOOSE framework also includes several systems to assemble unique workflows and coupling amongMOOSE-based applications. In particular, the MultiApp and Transfer systems are widely used to assemble different MOOSE-based or MOOSE- wrapped physics applications together to perform loosely or tightly coupled multiphysics simulations. The National Reactor Innovation Center’s (NRIC’s) Virtual Test Bed (VTB) [3] hosts publicly available nuclear reactor multiphysics simulation examples which leverage MOOSE’s MultiApp system to meet the modeling needs of different reactor types. The flexibility and robustness of coupling provided by MOOSE permits rapid development of coupled physics models for a wide range of reactor types and events.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Design of a Thermal Precipitator for the Characterization of Smoke Particles from Common Spacecraft Materials

A thermal precipitator (TP) was designed to collect smoke aerosol particles for microscopic analysis in fire characterization research. Information on particle morphology, size and agglomerate structure obtained from these tests supplements additional aerosol data collected. Modeling of the thermal precipitator throughout the design process was performed with the COMSOL Multiphysics finite element software package, including the Eulerian flow field and thermal gradients in the fluid. The COMSOL Particle Tracing Module was subsequently used to determine particle deposition. Modeling provided optimized design parameters such as geometry, flow rate and temperatures. The thermal precipitator was built and testing verified the performance of the first iteration of the device. The thermal precipitator was successfully operated and provided quality particle samples for microscopic analysis, which furthered the body of knowledge on smoke particulates. This information is a key element of smoke characterization and will be useful for future spacecraft fire detection research.

Smoke↗

Gas-Cooled High-Temperature Pebble-Bed Reactor Reference Plant Model Updates

This work presents the latest improvements to, and investigations performed with, the pebble-bed high-temperature gas-cooled reactor (PB-HTGR) reference plant models for the United States Nuclear Regulatory Commission. These models serve as the foundation for the future development of detailed design evaluation models based on license applications. The reference plant models have been developed with the Comprehensive Reactor Analysis Bundle, or BlueCRAB, which is the code suite proposed for non-light-water reactor systems safety analysis. It incorporates various simulation tools developed by the Nuclear Energy Advanced Modeling and Simulation program, including the Griffin code for reactor physics, the Pronghorn and SAM codes for core thermal fluids, the BISON code for solid conduction and fuel performance, and the SAM code for system analysis. The primary objective of the work that was performed was to assess BlueCRAB’s level of readiness for modeling a PB-HTGR. To do so, we first developed numerical models in BlueCRAB that include the key physics for this technology to ensure an adequate level of fidelity for modeling PB-HTGR core performance and for performing multiphysics simulations for equilibrium core conditions and different accident scenarios. Then we simulated transient scenarios, including depressurized and pressurized loss of forced cooling accidents, over-cooling, and control rod withdrawal events with delayed and prompt supercritical reactivity insertions. The analysis in this report includes comparisons of the 2D thermal fluid porous media models in Pronghorn and SAM, and comparisons of coupled SAM/Griffin/SAM and coupled Pronghorn/Griffin for depressurized and pressurized loss of forced cooling, over-cooling, and control rod withdrawal events. In addition, we compare 3D, 2D, and 0D/PKE neutronic models for the two control rod withdrawal scenarios with coupled Pronghorn/Griffin. The comparisons show that the BlueCRAB models lead to physically intuitive solutions for the scenarios examined. The changes in the various scalar and vector fields, such as neutron flux, power, temperature, density, pressure, and velocity, are within the expected ranges, and their distributions can be explained by the system response of the transients and the geometric and material variations. Several comparisons suggest that the porous media models in Pronghorn and SAM can lead to similar solutions, even though they are based on different methodologies. This work further highlights the need for flexible tools with various levels of fidelity to cover the breadth and depth of needs that may arise in future technical evaluations of the PB-HTGR. We believe that the BlueCRAB capabilities will be a significant asset for confirmatory analyses in order to resolve important safety questions.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Coupling of CTF and RELAP5-3D Within an Enhanced Fidelity Nuclear Power Plant Simulator

A robust and accurate multiphysics engineering simulator is being developed to model the core behavior and system response of pressurized water reactors. This simulator relies on the NESTLE and CTF computer codes to model the neutronics and thermal hydraulics (TH), respectively, inside the core on a nodal scale and on the Reactor Excursion and Leak Analysis Program—Three Dimensional (RELAP5-3D) to model the entire nuclear steam supply system. The RELAP5-3D model includes highly detailed nodalization and multidimensional flow modeling throughout the vessel. Previously, pin-resolved data generated via the Virtual Environment for Reactor Analysis core simulator were used to improve the accuracy of the NESTLE core predictions. The engineering simulator being developed as part of this work uses the 3KEYMASTER platform to couple the enhanced NESTLE model to a nodal-fidelity CTF model to balance run time with accuracy; NESTLE provides node-dependent powers to CTF, and CTF provides node-dependent coolant densities and fuel temperatures to NESTLE.An overlapping domain approach is used for the core TH in which RELAP5-3D provides core boundary conditions based on the system response and CTF provides a node-dependent coolant heating rate to the RELAP5-3D core solution. In the preliminary TH demonstration discussed in this paper, CTF and RELAP5-3D provided similar steady-state core predictions, indicating the hydraulic compatibility between the codes, as well as reasonable and expected behavior under hypothetical transient conditions. This provides an initial step in ongoing efforts toward a robust, multiscale TH/neutronics engineering simulator capability.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

MECHANISTIC MULTIPHYSICS MODELING OF CLADDING RUPTURE IN NUCLEAR FUEL RODS DURING LOSS-OF-COOLANT ACCIDENT CONDITIONS

The Loss of Coolant Accident (LOCA) is a design basis accident that is included as part of the safety analysis of nuclear power plants. As the nuclear industry desires to increase the cycle length and discharge burnup of existing nuclear power plants they must demonstrate safe operation during a LOCA on high burnup fuel. During a LOCA transient on high burnup fuel rods, the rods may undergo a process known as fuel fragmentation, relocation, and dispersal (FFRD). To permit dispersal, the cladding encapsulating the fuel must rupture with an opening size large enough to allow the fragmented fuel particles to release. Current licensing tools used by industry and the United States Nuclear Regulatory Commission are limited in geometric fidelity and materials that can be analyzed. These simulation tools generally employ a quasi-two-dimensional (1.5D or Layered1D) or 2D-RZ axisymmetric geometric representations exclusively. While a valid approach under some instances, there are times when important physics have an asymmetric behavior in the fuel rod. Examples include fuel fragmentation, thermal-hydraulic boundary conditions, and cladding rupture, all of which are important for LOCA analysis. As industry pursues burnup extensions it must be demonstrated that fuel dispersal can be mitigated or eliminated. To do this, an understanding of the rupture opening after cladding failure is required. This work presents the development of a model for predicting the size and location of the rupture opening in failed fuel rods during LOCA conditions using advanced modeling and simulation tools. In order to supply the rupture model with appropriate boundary conditions, improvements to fuel fragmentation, axial relocation and oxidation modeling were required. First, the eXtended Finite Element Method (XFEM) is used to mechanistically predict the number of fuel fragments that form due to material strength randomization, criteria for strength randomization, mesh density, power ramping rates and irradiation effects. These predictions with associated uncertainty were compared to empirical correlations developed for UO2 verifying that they can be used with increased confidence in subsequent axial relocation analyses. Secondly, a new first-of-its-kind Layered2D computational framework was developed that provides the ability to apply azimuthally varying boundary conditions while providing discrete layers to track fuel movement during the LOCA. An existing fuel axial relocation model developed for Layered1D was extended to work within the Layered2D framework. A large sensitivity study was performed on the initial version of the model to identify modeling parameters of particular importance, with the emissivity used for radiation after blowdown being the primary source of uncertainty. Then, a simplistic approach to incorporate mechanical degradation of the cladding due to oxidation was also developed to investigate the impact of reduced cladding thickness on predictions of the time to failure of cladding tubes. It was found that the cladding will typically rupture prior to a reduction in thickness that is sufficient to impact the rupture behavior. A model was then developed for predicting cladding rupture that transfers the cladding surface temperatures, rod internal and external pressures, fast neutron fluence, and fast neutron flux from a more detailed Layered1D, Layered2D, or 2D-RZ analysis to a 3D cladding only analysis. Comparisons of the rupture model to a few experiments indicate reasonable predictions. The rupture model was then applied to two accident tolerant fuel concepts (FeCrAl and Cr-coated Zircaloy) where it predicted that both ATF concepts would have smaller rupture openings and delayed rupture times than the standard Zircaloy-4 cladding material under identical loading conditions.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Enabling scientific machine learning in MOOSE using Libtorch

A neural-network-based machine learning interface has been developed for the Multiphysics Object-Oriented Simulation Environment (MOOSE). The interface relies on Libtorch, the C++ front-end of PyTorch, and enables an online interaction between modern machine learning algorithms and all the existing simulation, modeling, and analysis processes available in MOOSE. New capabilities in MOOSE include the native generation and training of artificial neural networks together with options to load pretrained neural networks in TorchScript format. Furthermore, the MOOSE stochastic tools module (MOOSE-STM) has been enhanced with neural network-based surrogate and reduced-order model generation options for efficient stochastic analyses. Lastly, a reinforcement learning capability has been added to MOOSE-STM for the interactive control and optimization of complex multiphysics problems.

97 MATHEMATICS AND COMPUTING↗

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↗

Towards verifiable cancer digital twins: tissue level modeling protocol for precision medicine

Cancer exhibits substantial heterogeneity, manifesting as distinct morphological and molecular variations across tumors, which frequently undermines the efficacy of conventional oncological treatments. Developments in multiomics and sequencing technologies have paved the way for unraveling this heterogeneity. Nevertheless, the complexity of the data gathered from these methods cannot be fully interpreted through multimodal data analysis alone. Mathematical modeling plays a crucial role in delineating the underlying mechanisms to explain sources of heterogeneity using patient-specific data. Intra-tumoral diversity necessitates the development of precision oncology therapies utilizing multiphysics, multiscale mathematical models for cancer. This review discusses recent advancements in computational methodologies for precision oncology, highlighting the potential of cancer digital twins to enhance patient-specific decision-making in clinical settings. We review computational efforts in building patient-informed cellular and tissue-level models for cancer and propose a computational framework that utilizes agent-based modeling as an effective conduit to integrate cancer systems models that encode signaling at the cellular scale with digital twin models that predict tissue-level response in a tumor microenvironment customized to patient information. Furthermore, we discuss machine learning approaches to building surrogates for these complex mathematical models. These surrogates can potentially be used to conduct sensitivity analysis, verification, validation, and uncertainty quantification, which is especially important for tumor studies due to their dynamic nature.

60 APPLIED LIFE SCIENCES↗

Establishing a process-structure-property-performance framework for SLS additive manufacturing through integrated multiscale modeling

This study presents a comprehensive suite of high-fidelity computational models that integrate multiscale and multiphysics simulations to capture the full Selective Laser Sintering (SLS) additive manufacturing process—from initial melting and solidification to mechanical response under external loads. Process simulations are linked with mechanical analysis through Representative Volume Elements (RVEs), establishing a process-structure–property-performance framework. The interaction between laser light and polyamide 12 (PA12) powder is modeled, accounting for laser characteristics and the optical, thermal, and geometrical properties of the powder. The heat source is incorporated into a heat transfer model, coupled with crystallization kinetics and densification models to predict material density and crystallinity. The porosity distribution from the densification model and crystallinity interpolated from experimental data are used to construct the RVEs. A multi-mechanism constitutive model is then calibrated using mechanical tests to predict the stress–strain response. Simulation results show good agreement with experimental data in terms of porosity, crystallinity, and mechanical performance when sufficient laser power (62 W or higher) is used. This research supports the inverse design of 3D-printed structures by introducing a high-fidelity framework that combines multiscale and multiphysics modeling with experimental calibration for predictive and performance-driven additive manufacturing.

SLS↗

X-ray Micro-Computed Tomography for Structural Analysis of All-Solid-State Battery at Pouch Cell Level

Characterizing the microstructure of all-solid-state batteries (ASSBs) during fabrication and operation is vital for their advancement, particularly as scaling to pouch cell levels introduces challenges in probing large-scale microstructural evolution. This work highlights the potential of synchrotron X-ray micro-computed tomography (sXCT) as a nondestructive, rapid (<30 min), and high-resolution technique for visualizing and quantifying key microstructural features, including overhang, porosity, contact loss, active surface area, and tortuosity, in all-solid-state pouch cells. The large field of view (up to millimeters) of sXCT enables detailed analysis at an industry-relevant scale, bridging the gap between laboratory research and commercial applications. Furthermore, integrating realistic sXCT-derived 3D models into multiphysics simulations could provide insights into chemo-mechanical degradation, particularly at the edges of the pouch cells, offering a pathway for designing robust, high-performance ASSBs. This perspective establishes sXCT as an indispensable tool for advancing both the understanding and the engineering of next-generation energy storage systems.

25 ENERGY STORAGE↗

Transient convective delayed neutron precursor of {sup 235}U for the molten salt reactor experiment

This work investigates the delayed neutron precursors from the fission of {sup 235}U in molten salt reactors. The six delayed neutron groups predict the spatial distribution of the advective transport for radioactive mass transfer in the molten-salt reactor experiment (MSRE). The Mole code, using the framework of the Multiphysics Object-Oriented Simulation Environment (MOOSE), was used to compute the delayed neutron concentration of the whole system. This approach can be used for analysis of reactivity in circulating conditions. The effect of delayed neutron concentrations on the static or dynamic behavior of the system in MSRE was analyzed. Using this approach, the pattern and validation of delayed neutron for a range of parameters of interest are reported and discussed herein. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

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

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

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Full-core high-burnup BWR LOCA fuel performance analysis and FFRD susceptibility

The susceptibility of the boiling water reactor (BWR) Limerick Unit 1 to fuel fragmentation, relocation, and dispersal during a postulated large-break loss-of-coolant accident (LBLOCA) was calculated using a multiphysics framework. The simulations include full-core, rod-resolved neutronic, thermal hydraulic, and fuel performance models using the VERA, TRACE, and BISON codes. This work focused on the transient BISON simulations, which include both the normal operation and LBLOCA periods in the same simulations. Cladding integrity was assessed using two correlations that are included with BISON. make page break Several new BWR-specific features were recently added to BISON. This work represents the first time these features have been included in a core-scale set of simulations. This study hence evaluates the performance of these new models for an operating reactor with realistic operating conditions. Simulation results showed that cladding integrity was maintained (i.e., no rods burst). Finally, future work to improve BWR and PWR predictions using this framework is suggested.

BISON↗