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This division promotes the development and timely introduction of fusion energy as a sustainable energy source with favorable economic, environmental, and safety attributes. The division cooperates with other organizations on common issues of multidisciplinary fusion science and technology, conducts professional meetings, and disseminates technical information in support of these goals. Members focus on the assessment and resolution of critical developmental issues for practical fusion energy applications.
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2024 ANS Annual Conference
June 16–19, 2024
Las Vegas, NV|Mandalay Bay Resort and Casino
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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.
Yuxuan Liu, Brendan Kochunas, Tat Nghia Nguyen, Hubert Ley, Richard Vilim
Nuclear Technology | Volume 208 | Number 12 | December 2022 | Pages 1832-1846
Technical Paper | doi.org/10.1080/00295450.2022.2092357
Articles are hosted by Taylor and Francis Online.
Advances in reducing operations and maintenance (O&M) costs are crucial to improving the viability of the nuclear energy industry. One of the important aspects to reduce the cost of maintenance activities in nuclear power plants is to automate equipment monitoring and fault diagnoses. As an inverse problem to fault diagnoses, finding a suitable population of sensors that enable a requisite degree of monitoring capability, preferably at low cost, is a prerequisite that ensures a successful monitoring and diagnosis capability. This work develops an optimization tool for the sensor assignment problem of thermal-hydraulic systems that minimizes the cost for a required diagnosing capability. The optimization is driven by a genetic algorithm (GA), with its parameters tuned by Bayesian optimization (BO). Compared to the conventional GA parameter-tuning approach based on experimental designs, the BO-tuned parameters show better performance for the test problem with various allocated computing resources. It is also verified that the BO-tuned parameters perform better for several problem variants based on the original test problem, which has practical values in meeting additional engineering goals in the sensor assignment process.