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The busyness of the nuclear fuel supply chain
Ken Petersenpresident@ans.org
With all that is happening in the industry these days, the nuclear fuel supply chain is still a hot topic. The Russian assault in Ukraine continues to upend the “where” and “how” of attaining nuclear fuel—and it has also motivated U.S. legislators to act.
Two years into the Russian war with Ukraine, things are different. The Inflation Reduction Act was passed in 2022, authorizing $700 million in funding to support production of high-assay low-enriched uranium in the United States. Meanwhile, the Department of Energy this January issued a $500 million request for proposals to stimulate new HALEU production. The Emergency National Security Supplemental Appropriations Act of 2024 includes $2.7 billion in funding for new uranium enrichment production. This funding was diverted from the Civil Nuclear Credits program and will only be released if there is a ban on importing Russian uranium into the United States—which could happen by the time this column is published, as legislation that bans Russian uranium has passed the House as of this writing and is headed for the Senate. Also being considered is legislation that would sanction Russian uranium. Alternatively, the Biden-Harris administration may choose to ban Russian uranium without legislation in order to obtain access to the $2.7 billion in funding.
Joshua Hanophy, Ben S. Southworth, Ruipeng Li, Tom Manteuffel, Jim Morel
Nuclear Science and Engineering | Volume 194 | Number 11 | November 2020 | Pages 989-1008
Technical Paper | doi.org/10.1080/00295639.2020.1747263
Articles are hosted by Taylor and Francis Online.
The computational kernel in solving the SN transport equations is the parallel sweep, which corresponds to directly inverting a block lower triangular linear system that arises in discretizations of the linear transport equation. Existing parallel sweep algorithms are fairly efficient on structured grids, but still have polynomial scaling, P1/d + M, for d dimensions, P processors, and M angles. Moreover, an efficient scalable parallel sweep algorithm for use on general unstructured meshes remains elusive. Recently, an algebraic multigrid (AMG) method based on approximate ideal restriction (AIR) was developed for nonsymmetric matrices and shown to be an effective solver for linear transport. Motivated by the superior scalability of the AMG methods (logarithmic in P) as well as the simplicity with which the AMG methods can be used in most situations, including on arbitrary unstructured meshes, this paper investigates the use of parallel AIR (pAIR) for solving the SN transport equations with source iteration in place of parallel sweeps. The results presented in this paper show that pAIR is a robust and scalable solver. Although sweeps are still shown to be much faster than pAIR on a structured mesh of a unit cube, pAIR is shown to perform similarly on both a structured and unstructured mesh, and offers a new, simple, black-box alternative to parallel transport sweeps.