On scalable liquid-metal MHD solvers for fusion breeder blanket multiphysics applications

On scalable liquid-metal MHD solvers for fusion breeder blanket multiphysics applications

On scalable liquid-metal MHD solvers for fusion breeder blanket multiphysics applications 150 150 UKAEA Opendata
UKAEA-STEP-PR(23)09

On scalable liquid-metal MHD solvers for fusion breeder blanket multiphysics applications

While substantial research effort has been made recently in the development of computational liquid-metal magnetohydrodynamics (MHD) solvers, this has typically been confined to closed-source and commercial codes. This work aimed to investigate some open-source alternatives. Two OpenFOAM-based MHD solvers, mhdFoam and epotFoam, were found to show strong scaling profiles typical of fluid dynamics codes, while weak scaling was impeded by an increase in iterations per timestep with increasing resolution. Both were found to accurately solve the Shercliff and Hunt flow problems for Hartmann numbers from 20 to 1000, except for mhdFoam which failed in the Hunt flow Ha = 1000 case. An inductionless MHD solver was implemented in the Proteus MOOSE application as a proof of concept, using two methods referred to as the kernel method and material method. The material method was found to converge with a wider range of preconditioners than the kernel method. Both methods were found to be inaccurate, with velocity lower than expected, and both failed to converge for high mesh expansion ratios. Future work will aim to build on these studies, exploring more advanced OpenFOAM MHD solvers as well as improving the Proteus MHD solver.

Collection:
Journals
Journal:
Plasma Physics and Controlled Fusion
Publisher:
IOP (Institute of Physics)