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DOE OSTI2023

Implementation of Distributed Memory Computing in MOSAIC to Enable Large 3D Simulations of Irradiated Concrete

The concrete biological shield (CBS) of light-water reactors protects workers and the surrounding environment by absorbing neutron and gamma irradiation emitted from the reactor core. The radiation dose increases with the CBS’s operational time and, in the long term, becomes significant enough to raise the question of irradiation effects on concrete—and particularly on the structural integrity of the CBS. Irradiation-induced damage has been identified as one of the main degradation mechanisms in the CBS. Neutron radiation causes the swelling of aggregate-forming minerals at different rates and amplitudes depending on the mineral’s nature. Silicate-bearing minerals such as quartz are particularly sensitive to neutron radiation and experience up to 17.8% volumetric expansion. Aggregates comprise several minerals with different orientations and are, therefore, subject to cracking as a result of mismatch strains. Additionally, the swelling of aggregates creates significant stresses in the surrounding cement paste matrix, which also results in crack formation. In parallel with the collection of characterization and irradiation test data, development of modeling and simulation tools for irradiated concrete is ongoing with the support of the US Department of Energy Office of Nuclear Energy’s Light Water Reactor Sustainability (LWRS) program. This effort resulted in the development and application of the fast-Fourier transform (FFT)–based code Microstructure-Oriented Scientific Analysis of Irradiated Concrete (MOSAIC) at Oak Ridge National Laboratory.

61 RADIATION PROTECTION AND DOSIMETRY↗

DOE OSTI2026

TRACE Input Modernization

This work presents a Tom’s Obvious Minimal Language (TOML)-based representation of input for the US Nuclear Regulatory Commission’s TRAC/RELAP Advanced Computational Engine (TRACE) thermal hydraulics code. Implemented using the Workbench Analysis Sequence Processor (WASP), the approach maps traditional TRACE input structures to a hierarchical format composed of named parameters, typed values, and native data collections. The resulting representation preserves TRACE’s existing modeling capabilities while providing a modern, structured interface for model development and management. WASP further extends TOML through a file import directive that supports modular model composition and reusable input organization. In addition, WASP provides extended array data entry convenience with various data repeat and interpolation capabilities. Examples of the new TOML syntax are provided for major TRACE input categories, including hydraulic components, heat structures, control systems, and trip logic. The TOML representation establishes a foundation for improved validation, tooling, automation, and model maintainability while remaining compatible with existing TRACE workflows. To facilitate migration to the TOML-based input format, the TRACE executable now supports conversion of native TRACE input into an intermediate JSON representation. A Python utility subsequently transforms the JSON data into an equivalent TOML model. Lastly, the TRACE executable now supports execution using TOML-formatted input.

Lefebvre, Robert A. [Oak Ridge National Laboratory↗

DOE OSTI2023

Opportunities for enhancing MLCommons efforts while leveraging insights from educational MLCommons earthquake benchmarks efforts

MLCommons is an effort to develop and improve the artificial intelligence (AI) ecosystem through benchmarks, public data sets, and research. It consists of members from start-ups, leading companies, academics, and non-profits from around the world. The goal is to make machine learning better for everyone. In order to increase participation by others, educational institutions provide valuable opportunities for engagement. In this article, we identify numerous insights obtained from different viewpoints as part of efforts to utilize high-performance computing (HPC) big data systems in existing education while developing and conducting science benchmarks for earthquake prediction. As this activity was conducted across multiple educational efforts, we project if and how it is possible to make such efforts available on a wider scale. This includes the integration of sophisticated benchmarks into courses and research activities at universities, exposing the students and researchers to topics that are otherwise typically not sufficiently covered in current course curricula as we witnessed from our practical experience across multiple organizations. As such, we have outlined the many lessons we learned throughout these efforts, culminating in the need for benchmark carpentry for scientists using advanced computational resources. The article also presents the analysis of an earthquake prediction code benchmark while focusing on the accuracy of the results and not only on the runtime; notedly, this benchmark was created as a result of our lessons learned. Energy traces were produced throughout these benchmarks, which are vital to analyzing the power expenditure within HPC environments. Additionally, one of the insights is that in the short time of the project with limited student availability, the activity was only possible by utilizing a benchmark runtime pipeline while developing and using software to generate jobs from the permutation of hyperparameters automatically. It integrates a templated job management framework for executing tasks and experiments based on hyperparameters while leveraging hybrid compute resources available at different institutions. The software is part of a collection called cloudmesh with its newly developed components, cloudmesh-ee (experiment executor) and cloudmesh-cc (compute coordinator).

58 GEOSCIENCES↗

DOE OSTI2021

Ground-based Transmission Spectroscopy with VLT FORS2: Evidence for Faculae and Clouds in the Optical Spectrum of the Warm Saturn WASP-110b

We present a ground-based optical transmission spectrum for the warm Saturn-mass exoplanet WASP-110b from two transit observations made with the FOcal Reducer and Spectrograph on the Very Large Telescope. The spectrum covers the wavelength range from 4000–8333 Å, which is binned in 46 transit depths measured to an averaged precision of 220 parts per million (ppm) over an averaged 80 Å bin for a Vmag = 12.8 star. The measured transit depths are unaffected by a dilution from a close A-type field dwarf, which was fully resolved. The overall main characteristic of the transmission spectrum is an increasing radius with wavelength and a lack of the theoretically predicted pressure-broadened sodium and potassium absorption features for a cloud-free atmosphere. We analyze archival high-resolution optical spectroscopy and find evidence for low to moderate activity of the host star, which we take into account in the atmospheric retrieval analysis. Using the AURA retrieval code, we find that the observed transmission spectrum can be best explained by a combination of unocculted stellar faculae and a cloud deck. Transmission spectra of cloud-free and hazy atmospheres are rejected at a high confidence. With a possible cloud deck at its terminator, WASP-110b joins the increasing population of irradiated hot-Jupiter exoplanets with cloudy atmospheres observed in transmission.

47 OTHER INSTRUMENTATION↗

DOE OSTI2023

Effects of Accident Thermal Loading on In-Plane Shear Behavior of Steel-Plate Composite Walls

Structural walls in safety-related nuclear facilities are required to be designed for seismic and accident thermal (due to postulated high-energy pipe break events) loading combination. Current U.S. and international codes provide limited guidance for analysis and design of walls for this loading combination. This paper describes the experimental results and observations from tests conducted on a laboratory-scale (1:4 to 1:5) test unit representing steel-plate composite (SC) walls subjected to combined in-plane (seismic) and accident thermal loading. The test unit was subjected to surface temperatures of up to 450°F in combination with cyclic in-plane loading. Results of similar experiments recently conducted in Japan are also summarized (with surface temperatures up to 570°F). Surface heating combined with the low thermal conductivity and high specific heat of concrete resulted in nonlinear thermal gradients through the thickness of the specimens. These nonlinear thermal gradients and the associated self- or internal restraint led to extensive concrete cracking. This concrete cracking reduced the initial and secant stiffness of the specimens. The initial stiffness of the heated specimens reduced to 30 to 40% of the initial stiffness of the control (unheated) specimen. The secant stiffness of the heated specimens reduced up to 50% of the secant stiffness of the control (unheated) specimen. However, the in-plane shear strength of the heated SC specimens was still approximately 10 to 30% greater than the nominal in-plane shear strength calculated, for the limit state of steel plate von Mises yielding, using AISC N690 equations and measured material properties. Evaluation of the experimental results and observations suggests that the in-plane shear strength of SC walls subjected to typical accident surface temperatures (up to 570°F) can be estimated conservatively using the current provisions of AISC N690. The stiffness for accident thermal loading combinations can be considered to reduce from cracked composite stiffness at ambient temperature to fully cracked—that is, steel-only stiffness as the surface temperature increases up to typical accident value.

Construction & Building Technology↗

DOE OSTI2023

Phonon-informed Neural Thermal Scattering (NeTS) Optimization for Crystalline Graphite and Beryllium Metal

Fast neutrons born from fission lose energy through scattering interactions in the process of slowing-down. As neutrons thermalize to the order of $k$ $b$ $T$ (where $k$ $b$ is the Boltzmann constant, and $T$ is the temperature of the medium), their de Broglie wavelength and energy approaches the order of inter-atomic spacing and quantized lattice vibrations, i.e., phonons. At thermal energies, the thermal scattering law (TSL), i.e., $S$($α, β$), captures crystal binding contributions to the total reaction rate, or cross section. This dimensionless material property describes the energy ($β$) and momentum ($α$) exchanges available in a medium. Currently, $S$($α, β$) is evaluated in the Full Law Analysis Scattering System Hub (FLASSH) code for discrete inputs and stored as ENDF/B File 7 for 0-phonon elastic (MT 2) and n-phonon inelastic (MT 4) processes. Further processing recasts $S$($α, β$) into cumulative distribution functions for sampling post-collision scattering kinematics. In practice, interpolation schemes are employed to access data between tabulated values. An improvement to this juncture of the nuclear data pipeline is supplying cross sections on-the-fly (OTF), as has been developed for the un-resolved resonance region to minimize non-physical interpolation errors. This capability may improve simulation accuracy for accident and transient analyses, where rapidly varying changes in temperature and pressure are difficult to predict beforehand. To do so, deep artificial neural networks (ANNs) can be employed which collapse non-linear, complex data into a lightweight dictionary of neural weights and biases. This has been successfully demonstrated for the hydrogen in light water $S$($α, β$) dataset in the form of a Neural Thermal Scattering (NeTS) module. In this work, the NeTS framework is extended to consider the impact of material-dependent dynamical features on optimal neural pre-processing and architecture design decisions, such as number of neurons per hidden layer, residual skip connections and neural depth. New NeTS modules for crystalline graphite and beryllium metal illuminate a novel correlation between dynamical nonlinearity and optimal neural parametrization when deploying $S$($α, β$) on-the-fly.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2022

Activation of lead coolant in Westinghouse lead fast reactor

The Westinghouse Lead-cooled Fast Reactor (LFR) is a medium-sized, passively safe, scalable reactor being developed by Westinghouse in collaboration with domestic and international organizations with the primary goals of reducing front-end capital cost and generating flexible and cost-competitive electricity while satisfying the highest standards in terms of safety and sustainability. An important aspect of new plant design is an assessment of activation level of its components so that an appropriate nuclear waste management plan can be established. As lead coolant is a distinguishing design feature of the LFR, its activation due to irradiation and the implications on establishing an appropriate waste disposal approach are important for engagement of project stakeholders, customers and nuclear safety regulators. This paper provides a brief description of the Westinghouse LFR design, a background on lead activation phenomenology, and then describes the methodology used for lead activation analysis performed with the computer code Serpent 2. It was determined that impurities naturally occurring in lead have the biggest contribution to lead activation. Corrosion and erosion products from the components immersed in lead can also be important contributors to lead activity and their impact can be limited by appropriate selection of materials and operating conditions. Polonium isotopes, resulting from bismuth generated from lead irradiation and its impurities, bring a notable contribution to the inhalation and ingestion doses during the plant operation and in the first years after the plant shutdown. However, it is not by far as important as for lead-bismuth coolant.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2024

Development of Thermal Scattering Law and Cross Sections of Hydrogen in Paraffin Wax

Paraffin wax is frequently used as a neutron moderator and shielding material. The main component of paraffin wax is straight-chain alkanes (n-alkanes). The deposition of paraffin wax is primarily attributed to the crystallization of n-alkanes. It is important to gain a deeper understanding of the mechanisms underlying the behavior of paraffin wax, which would impact the thermal scattering Law (TSL) and cross sections and affect the analysis of neutronic and critical systems. In this work, a classical molecular dynamics (CMD) simulation model was used in LAMMPS to create the TSL and cross sections at room temperature and pressure. To generate the required velocity autocorrelation functions (VACF), previously published data were used to validate the approach and models by comparing them with key model parameters. The phonon density of state (DOS) was calculated using Fourier transformation of the normalized VACF. This DOS was used as the primary input to estimate the TSL (S($a$, $β$)) and cross sections of hydrogen in paraffin wax. The TSL and cross sections of hydrogen were estimated using the Full Law Analysis Scattering System Hub (FLASSH) code. The cross section of hydrogen in paraffin wax is consistent with other hydrocarbon materials such as polyethylene with deviations due to structure in the lowest energy region.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2024

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↗

DOE OSTI2025

Enhancing Cluster Identification in Atom Probe Tomography Data Using Transfer Learning

Atom Probe Tomography (APT) is a powerful technique for visualizing the atomic-scale distribution of solutes in materials, but quantitative cluster analysis of APT datasets remains a challenge due to the need for subjective parameter selection in clustering algorithms. While distance-based and density-based methods such as HDBSCAN are widely used, their performance is highly sensitive to user-defined parameters, which undermines reproducibility and accuracy. This study proposes an image-based, deep learning-aided workflow for automating parameter selection and cluster detection in APT data analysis. By projecting 3D APT point clouds onto 2D planes, we leverage pretrained convolutional neural networks (ConvNeXt-Tiny and ResNet-50) through transfer learning to predict the number of clusters present in synthetic datasets. The output is used to guide K-means clustering and estimate HDBSCAN parameters, specifically minimum cluster size and minimum sample points. This approach reduces reliance on manual parameter tuning, improving consistency and scalability. The methodology demonstrates the feasibility of using image-based deep learning for interpreting complex spatial patterns in APT data, enabling faster and more objective analysis. The complete workflow and code are made publicly available to support reproducibility and future research.

Density-based clustering↗

DOE OSTI2024

Aeroelastic code comparison using the IEA 22MW reference turbine

Reference wind turbine designs and the associated aeroelastic models are widely used in both research and industry. Reference models representing future concepts are of particular interest. Current state of the art aeroelastic tools are relied upon to design the next generation of large wind turbines. However, modelling assumptions may be invalidated by upcoming very large turbines, and different aeroelastic tools may give inconsistent results. A 22MW turbine model has been defined as part of International Energy Agency (IEA) Wind Task 55 on Reference Wind Turbines and Farms to represent future turbines to be deployed in the 2030s. In this study, an aeroelastic model of this turbine has been created in four tools; Bladed, HAWC2, OpenFAST, and QBlade. Code comparisons are presented for steady state operation, linear stability analysis, and time domain power production simulations in steady and turbulent wind. Generally, the codes show a good agreement, but with some differences present in the linear stability analysis, periodic azimuthal variation, and time domain simulations. The models are a good basis for further study with the IEA 22MW turbine, and further code comparison exercises.

17 WIND ENERGY↗

DOE OSTI2020

Status Update on the High Precision Isotopic Measurements on High Burnup LWR Fuel in 2020

The US Department of Energy (DOE) Office of Nuclear Energy (NE) is currently investigating the feasibility of directly disposing dual-purpose (storage and transportation) canisters (DPCs) in a spent nuclear fuel (SNF) repository. Criticality during the repository performance period (10,000 years or more) is one of the major concerns related to direct disposal of DPCs, specifically as the system undergoes degradation in the repository environment and timeframe. Oak Ridge National Laboratory (ORNL) is developing an as-loaded criticality analysis methodology using full (actinides + fission products) burnup credit that exploits the inherent criticality margin associated with actual canister-specific loading configuration. Burnup credit criticality analysis requires validation of the depletion/decay codes used to generate the burned isotopic inventory of an assembly by comparing the code-predicted inventory with experimentally determined isotopic data. Currently, isotopic measurement data for boiling water reactors (BWR) SNF are limited, and additional measurements will be highly beneficial for BWR burnup credit analysis, which is essential to demonstrate disposability of BWR DPCs. Moreover, new pressurized water reactor (PWR) samples of isotopic measurements will expand the PWR sample population and consequently will greatly improve sample statistics. In turn, this will reduce uncertainty in the computational determination of the isotopic composition of commercial SNF and eliminate additional penalties currently used for lack of data. As part of the isotopic analysis task, eight diverse, high burnup (HBU) samples from several PWR rods are being dissolved and isotopically analyzed to provide high-quality measurement data for PWR SNF to reducing the uncertainties associated with PWR isotopic depletion validation. The isotopics of interest focus on nuclides important to burnup credit, shielding, and decay heat in PWR SNF. Additionally, eight high burnup BWR fuel samples from the Limerick nuclear power plant have been identified for measurement to support reducing uncertainties associated with BWR isotopic depletion validation.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2023

Investigations of Baryon Spectroscopy via Electromagnetic and Hadronic Scattering (Final Report, May 1, 2019 to August 15, 2021)

The principal goal of this project is the experimental and phenomenological study of baryon spectroscopy. The P.I.’s group currently consists of himself and one student, Mr. Haoran Sun. Haoran’s project involves a new coupled-channel partial-wave analysis of all available world data for the reactions $K^0_Lp → K^0_Sp, K^+p → K^+p, K^+n → K^0p, K^0p → K^+n$, and $K^+n → K^+n$. The analysis of Mr. Sun is related to a conditionally approved proposal to develop a secondary $K^0_L$ beamline in Hall D at JLab, to be used with the GlueX setup. Mr. Sun’s analysis will establish some of the software codes necessary to analyze some of the data that could be measured at this facility. More importantly, the analysis will provide new experimental constraints on important background $\textit{KN}$ reactions, which are needed in order to help understand data that involve formation of Λ$^{\ast}$ and Σ$^{\ast}$ resonances.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2020

Low- n global ideal MHD instabilities in the CFETR baseline scenario

This article reports an evaluation on the linear ideal magnetohydrodynamic (MHD) stability of the China Fusion Engineering Test Reactor (CFETR) baseline scenario for various first-wall locations. The initial-value code NIMROD and eigen-value code AEGIS are employed in this analysis. Despite the distinctly different approaches in modeling the scrape off layer region, the dominant growth in each of the low-n (n=1–10) modes are consistent between the two codes. We report the higher-n modes are dominated by ballooning modes and localized in the pedestal region, while the lower-n modes have more prominent external kink components and broader mode profiles. The influence of the plasma-vacuum profile and wall shape are also examined using NIMROD. In the presence of a resistive wall, the low-n ideal MHD instabilities are further studied using AEGIS. For the designed first-wall location, the n=1 resistive wall mode is found to be unstable, which could be fully stabilized by uniform toroidal rotation above the 2.9% core Alfven speed.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2025

Structural Design and Modeling of MARVEL Primary Coolant System Using the ASME Section III, Division 5, Code

This paper presents the structural design and supporting analysis for the Microreactor Applications Research Validation and Evaluation (MARVEL) primary coolant system (PCS) using the American Society of Mechanical Engineers (ASME) Boiler and Pressure Vessel Code Section III, Division 5, rules. MARVEL is a liquid metal–cooled microreactor intended to provide experimental capabilities for the rapid testing and development of microreactor technologies. The PCS utilizes high-temperature sodium-potassium liquid metal as the primary coolant and operates at a design temperature of 570°C, necessitating the consideration of creep-related failure mechanisms. The base metal for the PCS is 316H stainless steel, and the weldments are made with a 16-8-2 filler. The design approach incorporates the current base code rules along with ASME code cases N-924, N-861, and N-862 to address primary load, ratcheting, and creep-fatigue evaluations, respectively. The reactor’s operation involves complex thermal and mechanical interactions due to natural convective flow and differential thermal expansion between components. In conclusion, this paper discusses the structural engineering challenges encountered, such as managing thermal stresses in the distribution plenum and guard vessel, and outlines the strategies implemented to meet the code requirements, including design modifications and operational constraints.

21 - SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLAN↗

DOE OSTI2021

Commercial Building Energy Code Field Study (Final Report)

What is the dollar value of increasing compliance with the energy code? Ultimately, this is the question that policy makers, funders, and program implementers care about. With this in mind, Pacific Northwest National Laboratory (PNNL) developed a new methodology capable of determining how much energy cost savings could potentially be gained through better compliance with the code (Rosenberg et al. 2016). On March 2, 2016 DOE issued Funding Opportunity Announcement (FOA) Number DE-FOA-0001532, requesting proposals to develop and test a methodology for identifying the commercial energy code requirements that can provide the maximum cost-effective energy and cost savings through increased compliance. Awarded to the Institute for Market Transformation, this report summarizes the development and testing of a commercial code compliance methodology, including a summary of results, statistical analysis of sample, and best practices for others implementing a commercial energy code compliance field study.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2024

Assurance of Reasoning Enabled Systems (ARES)

ARES was in part motivated by the determination of President’s Council of Advisors on Science and Technology (PCAST) on May 13th, 2023 that published a set of inquiries: In an era in which convincing images, audio, and text can be generated with ease on a massive scale, how can we ensure reliable access to verifiable, trustworthy information? How can we be certain that a particular piece of media is genuinely from the claimed source? What technologies, policies, and infrastructure can be developed to detect and counter AI-generated disinformation? In an effort to automatically analyze and patch/optimize code the work in this report describes various neural Machine Learning (ML) analysis engine implementations to assist in situations where source code is deficient or completely lacking to decompile (lift) binary code to ’C’. The goal is to gradually reduce human intervention. To this end, two Large Language Model (LLM) variants (Code LLama 2, LLama 3.1 and Starcoder1, Starcoder 2) where finetuned with ’before/after’ code pairs on the OpenBLAS library. LLama trained on the lowering process, Starcoder trained on the lifting process with National Security Agency’s (NSA) open-source Ghidra decompiler assist. The inferencing test results indicate correctness for only very short sequences for Starcoder 2. Moving forward, the experiments conclude with a set of recommendations of required resources and technologies

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2024

Initial Development of Fusion Magnet Simulation Capabilities for Performance and Safety Evaluation Using the MOOSE Framework

Fusion energy holds the promise of being a transformative technology as a carbon-neutral, sustainable source of energy. Whole device modeling and the development of fusion digital twins will be increasingly important for emerging fusion device concepts at both national laboratories and within the commercial fusion industry. However, meeting the challenge of whole device modeling of fusion energy devices requires robust, multiphysics, multiscale modeling and simulation technologies capable of running on large-scale supercomputers. Detailed analysis of individual systems at-scale is also required to ensure safe and efficient operation as well as provide the safety basis for future device designs and licensing activities. In a tokamak, toroidal and poloidal magnets confine and shape the fusion plasma to promote the fusion reaction. High plasma temperatures and high magnetic field requirements in modern design concepts (leading to high amounts of energy stored within each magnet) impose electrical, thermal, and mechanical loads on the magnet components, which in turn impacts the safety considerations of the magnet and their supporting systems. Idaho National Laboratory (INL) has a history of working in this space, including development and benchmarking of the Magnetic System Circuitry Analysis Program (MSCAP) and Magnet Arcing (MAGARC) codes to study magnet quench events; notably, MAGARC was used to study quenching during the ITER Engineering Design Activity. However, these legacy codes and capabilities are not parallel and scalable, and new tools are required for future advances in this area, which leads to the INL-developed Multiphysics Object-Oriented Simulation Environment (MOOSE) framework. Developed originally for fission reactor systems under United States Department of Energy, Office of Nuclear Energy modeling and simulation programs, the MOOSE framework has been well-suited to multiscale, multiphysics modeling and simulation needs for nuclear systems. The framework is open-source, well-tested, under continuous development and deployment, and developed to a Nuclear Quality Assurance, Level 1 software quality standard. MOOSE has also been used in the fusion space previously in several projects: INL’s Tritium Migration Analysis Program, Version 8 (TMAP8) for tritium migration, UK Atomic Energy Authority’s A Unified Resource for OpenMC (fusion) Reactor Applications (AURORA) code for fusion thermo-mechanical and neutronics analysis, and Argonne National Laboratory’s Cardinal for high-fidelity computational fluid dynamics and neutronics. However, to model superconducting magnets, several MOOSE enhancements are required: additions to the current MOOSE electromagnetic capabilities, new material libraries for superconductors of interest (such as YBCO), as well as fusion-specific models for thermo-mechanics. This talk will discuss initial development activities to build these capabilities in MOOSE, focusing on initial validation and benchmarking activities. Proposed coupling workflows and future work to support the simulation of fusion magnets and magnet structural assemblies for performance and safety evaluation in MOOSE will also be discussed.

70 - PLASMA PHYSICS AND FUSION TECHNOLOGY↗