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Spent fuel recycling and conditioning topic of U.S.-Japan meeting
Officials with the Department of Energy’s Office of Environmental Management discussed spent nuclear fuel recycling and conditioning with counterparts from Japan during the 13th U.S.-Japan Technical Meeting of the Civil Nuclear Energy Research and Development Working Group, held recently in Santa Fe, N.M.
William C. Dawn, Scott Palmtag
Nuclear Science and Engineering | Volume 197 | Number 12 | December 2023 | Pages 3138-3159
Regular Research Article | doi.org/10.1080/00295639.2023.2189510
Articles are hosted by Taylor and Francis Online.
The Microreactor Exascale eZ CALculation (MEZCAL) tool has been developed to accurately and efficiently solve the neutron transport equation in general, unstructured meshes to support the design and modeling of microreactors. MEZCAL solves the self-adjoint angular flux form of the neutron transport equation using the finite element method. As the neutron transport equation is computationally expensive to solve, MEZCAL is designed to efficiently use exascale computing architectures, with an emphasis on graphics processing unit computing. To leverage existing tools, MEZCAL is built using the MFEM library and uses solvers from HYPRE, PETSc, and SLEPc. Verification of the neutron transport solver in MEZCAL is demonstrated with the solution to a one-dimensional cylindrical problem that has a semi-analytic solution. After verification, a realistic microreactor based on the MARVEL microreactor design is modeled using MEZCAL. Spatial and angular refinement results are presented for a two-dimensional model of the MARVEL microreactor, and the eigenvalue is converged to approximately 60 pcm. This convergence required a very fine mesh and more than 3.76 Billion Degrees Of Freedom (BDOF). Preliminary results are also presented for a three-dimensional model of the MARVEL microreactor. Finally, a weak scaling study is performed to investigate how the methods in MEZCAL will scale for larger problems with the next generation of exascale computing architectures.