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Division members promote the advancement of mathematical and computational methods for solving problems arising in all disciplines encompassed by the Society. They place particular emphasis on numerical techniques for efficient computer applications to aid in the dissemination, integration, and proper use of computer codes, including preparation of computational benchmark and development of standards for computing practices, and to encourage the development on new computer codes and broaden their use.
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2024 ANS Annual Conference
June 16–19, 2024
Las Vegas, NV|Mandalay Bay Resort and Casino
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Nuclear Science and Engineering
June 2024
Nuclear Technology
Fusion Science and Technology
Latest News
Securing the advanced reactor fleet
Physical protection accounts for a significant portion of a nuclear power plant’s operational costs. As the U.S. moves toward smaller and safer advanced reactors, similar protection strategies could prove cost prohibitive. For tomorrow’s small modular reactors and microreactors, security costs must remain appropriate to the size of the reactor for economical operation.
Eduardo Iraola, José M. Nougués, Lluís Batet, Josep A. Feliu, Luis Sedano
Fusion Science and Technology | Volume 80 | Number 3 | May 2024 | Pages 374-390
Research Article | doi.org/10.1080/15361055.2023.2260238
Articles are hosted by Taylor and Francis Online.
Nuclear fusion depends on tritium breeding and self-sufficiency. Tritium represents a hazard due to its radioactivity and migration properties. Because of these difficulties, ITER, the largest fusion experiment so far, relies on a conservative static procedure to monitor the tritium inventory. Future commercial fusion plants can avoid operation halts if a dynamic monitoring strategy proves itself valid. Tritium plant models have been developed for this kind of monitoring and analysis task, but sensor accuracy and reliability are an issue still to be addressed, and the path to dynamic monitoring remains unclear. The present work shows the modeling procedure of the Tokamak Exhaust Processing system in a commercial simulator, Aspen HYSYS, to reproduce the inventories, streams, process conditions, and compositions of this subsystem during operation. The model is verified in a steady-state scenario using data from the available literature. A demonstration of such a tritium plant subsystem shows meaningful value for several reasons. First, this process has not been modeled before in commercial dynamic simulators, which are typically used in the process industry. It will also allow new stakeholders to participate in future fusion-related projects. Second, it will play a key role in industry-like tritium process monitoring, in which the new model will act as a digital twin of the plant. Data-driven diagnostics can be fueled by model data, helping engineers to generate additional data that could otherwise be expensive to get directly from the plant. For these reasons, models will represent an essential part of a dynamic monitoring system, necessary for feasible fusion projects.