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At least 271 records · Page 15

FY25 Theory and Simulation Performance Target: Development of an integrated modeling framework for fusion reactor design and assessment (Final Report)

This report documents the FY25 Theory and Simulation Performance Target (TSPT) of developing an integrated modeling framework for fusion reactor design and assessment (FREDA). Over Q1-Q4, new capabilities were developed across both plasma and engineering domains and demonstrated on an example representation of a Compact Advanced Tokamak with a Dual Cooled Lead Lithium blanket. This represents a first-of-a-kind demonstration of coupled core-to-wall-to-engineering for a reactor. Self-consistent CESOL workflows were applied to provide core, pedestal, and SOL prediction; new modules were developed for energetic particle stability (FAR3D) and transport (TGLF-EP) analysis; and boundary plasma modeling (SOLPS-ITER, BOUT++/Hermes-3) was expanded to evaluate wall and divertor heat fluxes and interface with engineering thermal analysis. A parameterized CAD tool, TRACER, was expanded to generate medium-fidelity divertor, blanket, and coil geometries; OpenFOAM and Diablo workflows were applied for first-wall and divertor thermal analyses with helium cooling; and reduced-order models were created for high-mass-flux divertor cooling. Magnet multiphysics capabilities were verified between Elmer, Diablo, and a new MFEM-based solver, and workflows enable stress, thermal, and neutron-fluence analysis of TF coils with neutronics-driven heating. Nuclear and blanket analysis workflows were demonstrated, including tritium breeding, transport, and CFD-informed thermo-mechanical assessment. Preliminary multi-fidelity uncertainty quantification workflows were applied to boundary modeling codes and shown to achieve variance reductions with fewer high-fidelity boundary simulations. Key findings highlight the challenges of resolving the ITEP gap to find suitable balance between wall and divertor loads, neutron heating, and practical limits of PFC cooling. Next step priorities are to develop automated workflows to check boundary code convergence and detachment, implement tighter physics-engineering CAD provenance tracking, and inclusion of plasma-material interface models for SLAG and tungsten cracking behavior. Collectively, these developments establish sophisticated capabilities for predictive, multi-fidelity, whole-device modeling that integrates plasma physics, materials, magnets, and nuclear engineering to guide pathways to viable Fusion Pilot Plant design points.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Enhancing EnergyPlus capabilities to model dynamic building envelopes using python plugin

Nearly half of the energy consumption in the United States is related to buildings, resulting in an urgent need to develop innovative technologies to improve building energy efficiency. Dynamic building envelopes, comprising switchable insulation and thermal energy storage materials, have been proposed recently as a promising solution to reduce buildings' heating and cooling loads by thermally coupling the indoor environment with the ambient environment when beneficial while decoupling them when outdoor conditions are not favorable. Although various related technologies are still underway, the whole-building energy modeling tools, like EnergyPlus, do not have the capability to simulate the transient and dynamic nature of dynamic envelope materials and components to accurately predict their impact on building energy use. The objective of this study is to formulate a method in EnergyPlus simulation engine to model multilayer envelopes, comprising dynamic building materials with variable thermophysical properties, and discuss the changes made to the program using a Python plugin. Furthermore, the thermal performance of the dynamic envelopes using the proposed method is compared and verified with the results from a well-established commercial code, COMSOL Multiphysics. A parametric assessment is also conducted to evaluate the energy efficiency benefits of dynamic envelopes in a single-family residential building, demonstrating total annual energy savings up to 11.6 %, when a dynamic envelope operates alone, and up to 18.2 % when it is combined with a thin layer of phase change material as a thermal storage medium. Finally, a United States wide energy efficiency assessment is presented to showcase the geographical spread of the energy savings. The method designed and implemented in this study provides the researchers with the ability to implement their dynamic insulation methods in EnergyPlus and evaluate the whole building energy impact.

25 ENERGY STORAGE↗

Development of SAM Code Capabilities for Safety Analysis of GCR Air-ingress Events

Air-ingress following a depressurized loss-of-forced-cooling (DLOFC) event is a challenging, multiphysics safety scenario for High-Temperature Gas-Cooled Reactors (HTGRs), involving coupled gas composition transport, buoyancy-driven flow redistribution, graphite oxidation, and structural heat-up. Despite its importance — air ingress is a key scenario identified in the PIRT process for the HTGRs — existing system-level safety codes have lacked the integrated capability to simulate the complete event sequence with high confidence. This report documents the development, validation, and demonstration of three new capabilities in the SAM code to address this gap: (1) a multi-component gas mixture flow model with binary diffusion to track the helium-air composition and its effect on system density and flow; (2) a 0-D graphite oxidation model based on the Roes correlation, including oxygen consumption and exothermic heat release; and (3) an isentropic critical flow model for accurate representation of primary system depressurization through a break. These capabilities are validated against two benchmark experiments. The NSTF heavy-gas ingress experiment validates the multi-component flow model: SAM correctly reproduces the rapid buoyancydriven flow stagnation and subsequent natural circulation recovery driven by composition-dependent density changes. The NACOK graphite oxidation experiment validates the oxidation model: SAM predicts a bottom-level graphite weight loss of 25%, in close agreement with the measured 24%, and reproduces the strong axial nonuniformity and block-geometry dependence of oxidation, at a level comparable to the SPECTRA and TINTE codes. The validated capabilities are then exercised together in an integrated, reactor-scale simulation of a DLOFC air-ingress transient in a simplified HTR-PM pebble-bed reactor. In a single calculation spanning approximately 8 days, SAM reproduces the complete accident sequence: rapid depressurization, densityand diffusion-driven air ingress over ˜15 hours, onset of buoyancy-driven natural circulation, exothermic graphite oxidation with a peak fuel temperature at ˜62 hours, and eventual passive cooldown. These results demonstrate that SAM now provides the nuclear community with a preliminarily validated, modern systemlevel tool for HTGR air-ingress safety analysis, filling a recognized capability gap. Future extensions to broaden species tracking, improve oxidation chemistry, and refine the reactor model are discussed.

Yang, Gang↗

A Fundamentally New Coupled Approach to Contact Mechanics via the Dirichlet‐Neumann Schwarz Alternating Method

Contact phenomena are crucial for understanding the behavior of mechanical systems. However, existing computational approaches for simulating mechanical contact often face numerical challenges, such as inaccurate physical predictions, energy conservation errors, and unwanted oscillations. Here, we introduce an alternative technique for simulating dynamic contact based on the non‐overlapping Schwarz alternating method, originally developed for domain decomposition. In multibody contact scenarios, this method treats each body as a separate, non‐overlapping domain and prevents interpenetration using an alternating Dirichlet–Neumann iterative process. This approach has a strong theoretical foundation, eliminates the need for contact constraints, and offers flexibility, making it ideal for multiscale and multiphysics applications. We conducted a numerical comparison between the Schwarz method and traditional methods, such as the Lagrange multiplier and penalty methods, focusing on a benchmark impact problem. Our results indicate that the Schwarz alternating method outperforms traditional methods in several key areas: it provides more accurate predictions for various measurable quantities and demonstrates exceptional energy conservation capabilities. To address unwanted oscillations in contact velocities and forces, we explored various algorithms and stabilization techniques, ultimately opting for the naïve‐stabilized Newmark scheme for its simplicity and effectiveness. Additionally, we validated the efficiency of the Schwarz method in a three‐dimensional impact problem, highlighting its inherent capacity to accommodate different mesh topologies, time‐integration schemes, and time steps for each interacting body.

Schwarz alternating method↗

INL Poster - Juan Barrera Salazar

Generation IV nuclear reactors introduce several advantages and benefits in terms of safety and efficiency when compared with their predecessors from previous generation. This is due, among many things, to the use of innovative forms of fuel and coolant, different from the conventional ones used in the last decades. Given that these upcoming designs utilize emerging technologies, the related instrumentation is also in the process of being developed; therefore, it is necessary to establish the sensitivity requirements and the effects of uncertainty on different properties of the components and elements of the reactor designs. This report presents the results of simulations that quantify the impacts of the uncertainties of four thermophysical properties of the refrigerant salt (LiF-BeF2) for the Kairos Power benchmark model (g-FHR) for steady state making use of the Sobol’ method through polynomial chaos surrogate modeling. The properties of the salt to which uncertainty was evaluated were density, dynamic viscosity, thermal conductivity and heat capacity. This study was carried out using the Griffin/Pronghorn multiphysics model under the computational resources of the Idaho National Laboratory (INL) High Performance Computing (HPC). The results indicate a weak dependence of the uncertainty of thermal conductivity on the quantities of core pressure drop and core outlet temperature.

21 - SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLAN↗

On the uncertainties in helium generation predictions for fission and fusion alloys

With ongoing advances in fusion and advanced fission reactors, quantifying irradiation effects in materials is critical. Transmutation-induced helium in cladding and structural materials can drive swelling and embrittlement, thereby reducing these components’ lifespans. Yet most studies ignore the considerable uncertainties in predicting helium generation rates. In this work, we created a code wrapper, F-SCATTER, that automatically performs simulations in FISPACT-II. We used this tool to investigate potential variance in helium generation rate, or He/dpa, calculations based on deviations in alloy composition, irradiating neutron flux spectrum, computational methodology, and nuclear data sources. We used 12 wt% Cr HT9 steel as the reference case and observed a 6.5%–98.3% He/dpa spread based on compositional variation within a single chemical specification, a 1.8%–11.5% He/dpa variation upon the incorporation of a 15% artificial uncertainty in flux at each energy, and a He/dpa difference as high as 231% when using ENDF/B-VIII.0 versus TENDL-2021 data libraries. Similar results were found for other prominent iron-based alloys, including Grade 91, castable nano-structured alloy, and 316H—where additional variations exist based on reactor type (e.g. thermal, fast, or fusion) and alloying elements such as carbon, nitrogen, and nickel. Based on the simulated results, we conclude that a significant part of the heat-to-heat variability in swelling responses of Fe-based alloys can be driven by impurity content in alloy compositions, and, therefore, chemical control should be a key element in supply chain design for advanced nuclear energy systems. Furthermore, we provide critical recommendations on best practices for evaluating and reporting helium production and lattice damage rates when computing predictions with multiphysics programs such as FISPACT-II.

FISPACT-II↗

A Refined BISON-Griffin Workflow For Designing Targeted TRISO Transient Experiments In The Transient Reactor Test Facility

U.S. industry is expected to deploy tristructural isotropic (TRISO) particle fuel technologies for commercial reactors within the next decade. In our previous work, we defined a preliminary transient design space for TRISO fuels, identified potential gaps in the available data, and began to develop multiphysics modeling tools that could be applied to design targeted Transient Reactor Test Facility (TREAT) experiments to fill these gaps. This work builds on that foundation by (1) updating BISON fuel performance and Griffin reactor physics models to reflect the current TREAT experiment tube and capsule designs,(2) coupling the codes to improve the accuracy and usability of the transient design analyses, and (3) demonstrating their use over an expanded design space that includes fuel burnup. The simulated mechanical responses of the TRISO particles were complex functions of fission product accumulation, fission gas release, and irradiation-induced dimensional change in the pyrolytic carbon layers. Predicted tangential stresses in particle silicon carbide layers were least compressive for preheated tests involving fresh fuels but remained compressive throughout the ranges of temperature, heat rate, and burnup considered in this work. Finally, comparisons between the potential TREAT transients and historical test reactor irradiations showed that the TREAT tests would produce significantly lower average energy deposition rates, yielding less severe transients with greater relevance to near-term commercial applications. Use of these predictive capabilities has the potential to increase the value of each test, improving the overall efficiency and cost effectiveness of transient testing for TRISO and other advanced fuels.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Building a new multiphysics workflow in MOOSE: application to tritium migration, trapping and advection in TMAP8

Fusion devices are anticipated to produce and consume several kilograms of tritium per year. This rare fuel resource is both highly mobile and radioactive, making tracking inventories a priority for operation and safety. The fusion safety program at the Idaho National Laboratory has been developing the Tritium Migration and Analysis Program (TMAP), of which the latest version is a MOOSE-based application. TMAP8 is verified against its predecessors and possesses additional multi-dimensional tritium migration modeling capabilities. As we extend its capabilities towards both whole device (in multiple dimensions) and whole plant (with multiple components) simulations, the syntax of inputs must become compact, descriptive, compatible with quality assurance processes, and as error-proof as achievable. The new Physics system developed MOOSE can set up equations and instantiating them on plant components. The system permits the automatic definition of complex discretization with a consistency between object parameters achieved programmatically. The Physics system can currently instantiate the equations for heat conduction and Navier Stokes weakly compressible flow. In MOOSE-terms, it automates the definition of kernels, boundary conditions, and several core and helper materials and fields. As part of this effort, Physics classes were developed for tritium migration, trapping and advection within either a multi-dimensional Navier Stokes fluid dynamics simulation, or a 1D thermal hydraulics piping system. In this presentation, we will showcase the new syntax, its application to several verification and validation cases which were already studied using the classical TMAP8 syntax, and a demonstration of the new coupling capabilities for the migration of tritium into blanket coolant channels and the subsequent advection into the coolant loop.

70 - PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Refinement and demonstration of a coupled BISON-Griffin workflow for designing targeted TRISO transient experiments in TREAT

The U.S. nuclear industry is expected to deploy tristructural isotropic (TRISO) particle fuel technologies for commercial reactors within the next decade. In previous work, we defined a preliminary transient design space for TRISO fuels, identified potential gaps in the available data, and began to develop multiphysics modeling tools that could be applied to design targeted Transient Reactor Test Facility (TREAT) experiments to fill these gaps. Here, this work builds on that foundation by (1) updating BISON fuel performance and Griffin reactor physics models to reflect the current TREAT experiment tube and capsule designs, (2) coupling the codes to improve the accuracy and usability of the transient design analyses, and (3) demonstrating their use over an expanded design space that includes fuel burnup. The simulated mechanical responses of the TRISO particles were complex functions of fission product accumulation, fission gas release, and irradiation-induced dimensional change in the pyrolytic carbon layers. The predicted tangential stresses in the particles' silicon carbide layers were least compressive for preheated tests involving fresh fuels but remained compressive throughout the ranges of temperature, heat rate, and burnup considered in this work. Finally, comparisons between the potential TREAT transients and historical test reactor irradiations showed that the TREAT tests would produce significantly lower average energy deposition rates, yielding less severe transients with greater relevance to near-term commercial applications. The use of these predictive capabilities has the potential to increase the value of each test, improving the overall efficiency and cost-effectiveness of transient testing for TRISO and other advanced fuels.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Adaptively remeshed multiphysical modeling of resistance forge welding with experimental validation of residual stress fields and measurement processes

Welding processes used in the production of pressure vessels impart residual stresses in the manufactured component. Computational modeling is critical to predicting these residual stress fields and understanding how they interact with notches and flaws to impact pressure vessel durability. Here, in this work, we present a finite element model for a resistance forge weld and validate it using laboratory measurements. Extensive microstructural changes, near-melt temperatures, and large localized deformations along the weld interface pose significant challenges to Lagrangian finite element modeling. The proposed modeling approach overcomes these roadblocks in order to provide a high-fidelity simulation that can predict the residual stress state in the manufactured pressure vessel; a rich microstructural constitutive model accounts for material recrystallization dynamics, a frictional-to-tied contact model is coordinated with the constitutive model to represent interfacial bonding, and adaptive remeshing is employed to alleviate severe mesh distortion. An interrupted-weld approach is applied to the simulation to facilitate comparison to displacement measures. Several techniques are employed for residual stress measurement in order to validate the finite element model: neutron diffraction, the contour method, and the slitting method. Model-measurement comparisons are supplemented with detailed simulations that reflect the configurations of the residual-stress measurement processes themselves. The model results show general agreement with experimental measurements, and we observe some similarities in the features around the weld region. Factors that contribute to model-measurement differences are identified. Finally, we conclude with some discussion of the model development and residual stress measurement strategies, including how to best leverage the efforts put forth here for other weld problems.

36 MATERIALS SCIENCE↗

Thermo-Mechanical Phase-Field Modeling of Fracture in High-Burnup UO2 Fuels Under Transient Conditions

This study presents a novel multiphysics phase-field fracture model to analyze high-burnup uranium dioxide (UO2) fuel behavior under transient reactor conditions. Fracture is treated as a stochastic phase transition, which inherently accounts for the random microstructural effects that lead to variations in the value of fracture strength. Moreover, the model takes into consideration the effects of temperature and burnup on thermal conductivity. Therefore, the model is able to predict crack initiation, propagation, and complex morphologies in response to thermal gradients and stress distributions. Several simulations were conducted to investigate the effects of operational and transient conditions on fracture behavior and the resulting cracking patterns. High-burnup fuels exhibit reduced thermal conductivity, elevating temperature gradients and resulting in extensive radial and circumferential cracks. Transient heating rates and temperatures significantly affect fracture patterns, with higher heating rates generating steeper gradients and more irregular crack trajectories. This approach provides critical insights into fuel integrity during accident scenarios and supports the safety evaluation of extended burnup limits.

Chemistry↗

Scalable Multiphysics Block Preconditioning for Low Mach Number Compressible Resistive MHD with Application to Magnetic Confinement Fusion

This study investigates multiphysics block preconditioners that are critical in devising scalable Newton–Krylov iterative solvers for longer time-scale fully implicit fluid plasma models. The specific model of interest is the visco-resistive, low Mach number, compressible magnetohydrodynamics (MHD) model. This model describes the dynamics of conducting fluids in the presence of electromagnetic fields and can be used to study aspects of astrophysical phenomena, important science and technology applications, and basic plasma physics. The specific application of interest that motivates this study is the macroscopic simulation of longer time-scale stability and disruptions of magnetic confinement fusion devices, specifically the ITER Tokamak. The computational solution of the governing balance equations for mass, momentum, heat transfer, and magnetic induction for resistive MHD systems can be extremely challenging. These difficulties arise from both the strong nonlinear, nonsymmetric coupling of fluid and electromagnetic phenomena as well as the significant range of time and length scales that the interactions of these physical mechanisms produce. To handle the range of time and spatial scales of interest, a fully implicit unstructured variational multiscale finite element formulation is employed. For the scalable solution of the Newton linearized systems, fully coupled block preconditioners are designed to leverage algebraic multigrid subsolves. In conclusion, results are presented for the strong and weak scaling of the method as well as the robustness of these techniques for a large range of Lundquist numbers.

97 MATHEMATICS AND COMPUTING↗

Q1 Report for FY25 Theory and Simulation Performance Target: Development of an integrated modeling framework for fusion reactor design and assessment

This report describes the work and activities carried out towards the completion of each of the following milestones in FY25 Q1: 1. Demonstrate workflow for generating self-consistent CESOL plasma profiles + first wall and divertor loading prediction and generate the CAT plasma and neutron loading needed for further engineering analysis: $/circ$ Initially run CESOL with SOLPS and map heat flux using simple HEAT method: ▪ Generate SOLPS grid for CAT reference case, ▪ Implement and apply ‘lower’ fidelity method of using HEAT-like analytic method to map SOLPS heat flux from charged particles to first wall, and ▪ Provide initial heat flux + neutron loading for further engineering analysis. 2. Demonstrate multiphysics magnet analysis: $/circ$ Demonstrate validation of the Elmer workflow by comparing induced stresses due to EM forces generated by TF coils using multiple codes.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Modeling and Design Parameter Optimization to Improve the Sensitivity of a Bimorph Polysilicon-Based MEMS Sensor for Helium Detection

Helium is integral in several industries, including nuclear waste management and semiconductors. Thus, developing a sensing method for detecting helium is essential to ensure the proper operation of such facilities. Several approaches can be used for helium detection, including based on the high thermal conductivity of helium, which is several times higher than air. This work utilizes the high thermal conductivity of helium to design and analyze a bimorph MEMS sensor for helium sensing applications. COMSOL Multiphysics software (version 6.2) is used to carry out this investigation. The sensor is constructed from poly-silicon and SiO 2 materials with a trenched cantilever beam configuration. The sensor is electrically heated, and its morphed displacement depends on the surrounding gas’s composition, which decreases in the presence of helium. Several factors were investigated to probe their effect on the sensor’s sensitivity to helium, including the thickness of the poly-silicon layer, the configuration of the trench, and the thickness and location of SiO 2 layer. The simulations showed that the best performance, up to 2 ppm helium detection level, can be achieved with thinner beams and medium trench lengths.

47 OTHER INSTRUMENTATION↗

Toward digital design at the exascale: An overview of project ICECap

High performance computing has entered the Exascale Age. Capable of performing over 1018 floating point operations per second, exascale computers, such as El Capitan, the National Nuclear Security Administration's first, have the potential to revolutionize the detailed in-depth study of highly complex science and engineering systems. However, in addition to these kind of whole machine “hero” simulations, exascale systems could also enable new paradigms in digital design by making petascale hero runs routine. Currently, untenable problems in complex system design, optimization, model exploration, and scientific discovery could all become possible. Motivated by the challenge of uncovering the next generation of robust high-yield inertial confinement fusion (ICF) designs, project ICECap (Inertial Confinement on El Capitan) attempts to integrate multiple advances in machine learning (ML), scientific workflows, high performance computing, GPU-acceleration, and numerical optimization to prototype such a future. Built on a general framework, ICECap is exploring how these technologies could broadly accelerate scientific discovery on El Capitan. In addition to our requirements, system-level design, and challenges, we describe some of the key technologies in ICECap, including ML replacements for multiphysics packages, tools for human-machine teaming, and algorithms for multifidelity design optimization under uncertainty. As a test of our prototype pre-El Capitan system, we advance the state-of-the art for ICF hohlraum design by demonstrating the optimization of a 17-parameter National Ignition Facility experiment and show that our ML-assisted workflow makes design choices that are consistent with physics intuition, but in an automated, efficient, and mathematically rigorous fashion.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Optical neural engine for solving scientific partial differential equations

Abstract Solving partial differential equations (PDEs) is the cornerstone of scientific research and development. Data-driven machine learning (ML) approaches are emerging to accelerate time-consuming and computation-intensive numerical simulations of PDEs. Although optical systems offer high-throughput and energy-efficient ML hardware, their demonstration for solving PDEs is limited. Here, we present an optical neural engine (ONE) architecture combining diffractive optical neural networks for Fourier space processing and optical crossbar structures for real space processing to solve time-dependent and time-independent PDEs in diverse disciplines, including Darcy flow equation, the magnetostatic Poisson’s equation in demagnetization, the Navier-Stokes equation in incompressible fluid, Maxwell’s equations in nanophotonic metasurfaces, and coupled PDEs in a multiphysics system. We numerically and experimentally demonstrate the capability of the ONE architecture, which not only leverages the advantages of high-performance dual-space processing for outperforming traditional PDE solvers and being comparable with state-of-the-art ML models but also can be implemented using optical computing hardware with unique features of low-energy and highly parallel constant-time processing irrespective of model scales and real-time reconfigurability for tackling multiple tasks with the same architecture. The demonstrated architecture offers a versatile and powerful platform for large-scale scientific and engineering computations.

Tang, Yingheng (ORCID:0009000153622546)↗

Comparison of spatial dynamics and point kinetics approaches in multiphysics modeling of the molten salt reactor experiment

In this work, we present validation test results of fully coupled neutronics and thermal-hydraulics models of the Molten Salt Reactor Experiment (MSRE) against experimental data of the zero power pump transients and the natural circulation tests at low power. To capture the strong coupling between neutronics and thermal-hydraulics due to fuel circulation, and to account for the delayed neutron precursor (DNP) distribution, the porous media thermal-hydraulics solver Pronghorn was fully coupled to the spatial neutron dynamics code Griffin, which solves the neutron diffusion equation, and to the 0-D point kinetics solver Squirrel, using a 2-D homogenized representation of the MSRE. The validation test results show very good agreement with experimental data for both point kinetics and spatial dynamics simulations, capturing the strong feedback effect and DNP losses in the MSRE. The 0-D code Squirrel accurately predicted the time-dependent behavior in the MSRE given the steady-state spatial dynamics solution of Griffin.

42 - ENGINEERING↗

A Full-Induction Magnetohydrodynamics Solver for Liquid Metal Fusion Blankets in Vertex-CFD

Multiphysics modeling of liquid metal fusion blankets, which produce tritium and convert energy of neutrons created via fusion reactions into heat, is crucial for predicting performance, ensuring structural integrity, and optimizing energy production. While traditional blanket modeling of liquid metal flows during normal steady operating conditions commonly employs the inductionless approximation of the magnetohydrodynamics (MHD) equations, transient scenarios, when the plasma-confining magnetic field varies on millisecond time scales, require a full-induction MHD approach that dynamically evolves the magnetic field via the time-dependent induction equation. This paper presents the formulation, implementation, and initial verification of a full-induction MHD solver integrated within the open-source Vertex-CFD framework, which aims to achieve tight multiphysics coupling, a flexible software design enabling easy extension and addition of physics models, and performance portability across computing platforms. The solver utilizes finite element spatial discretization, implicit Runge–Kutta time integration, and an inexact Newton method to solve the resulting discrete nonlinear system, leveraging Trilinos packages for efficient computation. Verification against selected benchmark problems demonstrates accuracy and robustness of the solver. Furthermore, when the solver is applied to an idealized blanket model in 2.5D and full 3D, results obtained with Vertex-CFD are in good agreement with recently published quasi-2D simulations. These findings establish a computational foundation for future simulations of transient MHD phenomena in liquid metal blankets with Vertex-CFD, and open avenues for future extensions and performance optimizations.

Endeve, Eirik [ORNL] (ORCID:0000000312519507)↗