Eric Cervi

Liquid metals such as lithium and lead–lithium eutectics are leading candidates for use as breeder and coolant materials in fusion blankets, where they enable both tritium breeding and efficient heat removal. In the presence of strong magnetic fields, magnetohydrodynamic (MHD) effects significantly influence flow distribution, pressure drop, and heat transfer, posing major challenges for blanket design and performance assessment. While high-fidelity computational fluid dynamics (CFD) tools exist for MHD analysis, there remains a lack of modern system-level analysis codes that integrate MHD effects with thermal–hydraulic and systems modeling.This paper presents recent developments at Argonne National Laboratory to address this gap through the implementation of MHD modeling capabilities in the System Analysis Module (SAM), a modern system analysis code built on the MOOSE framework. A reduced-order MHD modeling approach applicable to high Hartmann number and high interaction parameter flows is adopted, enabling efficient system-level simulations relevant to fusion liquid metal blankets. In parallel, MHD capabilities are being implemented in the high-performance CFD code NekRS to provide high-fidelity simulations for verification and model development.Analytical verification, code-to-code comparisons, and validation against historical experimental data from the Argonne Liquid Metal Experiment (ALEX) facility are presented for both square and round duct configurations under applied magnetic fields. The results demonstrate good agreement between SAM and NekRS predictions with analytical solutions in uniform magnetic fields; good agreement between SAM predictions with legacy MHD codes, and experimental measurements in varying magnetic fields. Ongoing and future work includes extension to insulating duct configurations, further NekRS development, and application to conceptual fusion blanket designs and ITER test blanket modules.

Magnetohydrodynamics (MHD) investigates the intricate relationship between electromagnetism and fluid dynamics, offering a complete insight into the behavior of conducting fluids under the influence of magnetic fields. This theory plays a pivotal role in the framework of magnetic confinement fusion, where it can be applied to describe both thermonuclear plasmas confined inside the vacuum vessel and operating fluids, such as liquid metals and molten salts, flowing within the blanket of future tokamaks. Currently, the state-of-the-art numerical modeling of MHD scenarios employs a multi-physics framework to examine the interplay between magnetic fields and thermal hydraulics; however, due to the complexity of the involved physics, detailed models are required, resulting in a significant computational burden. In this regard, reduced order modeling (ROM) techniques may represent a promising solution, as they enable approximating complex systems with lower-dimensional models. Indeed, ROM methodologies can significantly reduce the required computational time while maintaining accuracy in capturing the convoluted physics involved in fusion reactors, especially in the contexts of sensitivity analysis, uncertainty quantification, and control. Despite their potential, ROM methods are relatively under-explored within the MHD framework; this study applies ROM techniques to MHD scenarios, focusing on their capabilities and possible limitations. To this aim, the backward-facing step, which is well suited for exploring the effects of different magnetic fields on turbulent dynamics, is adopted as case study. In particular, this work evaluates the potentialities of the ROM approach in enhancing computational efficiency within the MHD domain. Each of the methods evaluated was effective in precisely reconstructing flow dynamics at any given time and across the full range of magnetic field values tested while significantly reducing computational costs compared to full-order simulations. Practically, this study demonstrates the feasibility to create simplified models that accurately represent the magnetohydrodynamic flows of fluids within the blanket.

The U.S. Department of Energy's Office of Scientific and Technical Information