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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.
Vincent A. Mousseau, Dana A. Knoll
Nuclear Science and Engineering | Volume 154 | Number 2 | October 2006 | Pages 174-189
Technical Paper | doi.org/10.13182/NSE06-A2624
Articles are hosted by Taylor and Francis Online.
A study of the temporal accuracy of a variety of first- and second-order time-integration methods applied to two-dimensional, multimaterial, nonequilibrium, radiation diffusion simulations is presented. These methods are categorized by their temporal order of accuracy, whether the algorithm includes operator splitting, and whether the algorithm includes linearizations. Results are presented that simultaneously measure accuracy and efficiency of the different methods on two different test problems. The two test problems are designed to represent an easy problem, where different approximations may be accurate, and a hard test problem that will stress the different solution algorithms. Results show the importance of being second-order accurate in time and the importance of time-step control.