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Division Spotlight
Materials Science & Technology
The objectives of MSTD are: promote the advancement of materials science in Nuclear Science Technology; support the multidisciplines which constitute it; encourage research by providing a forum for the presentation, exchange, and documentation of relevant information; promote the interaction and communication among its members; and recognize and reward its members for significant contributions to the field of materials science in nuclear technology.
Meeting Spotlight
International Conference on Mathematics and Computational Methods Applied to Nuclear Science and Engineering (M&C 2025)
April 27–30, 2025
Denver, CO|The Westin Denver Downtown
Standards Program
The Standards Committee is responsible for the development and maintenance of voluntary consensus standards that address the design, analysis, and operation of components, systems, and facilities related to the application of nuclear science and technology. Find out What’s New, check out the Standards Store, or Get Involved today!
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Latest News
TerraPower begins U.K. regulatory approval process
Seattle-based TerraPower signaled its interest this week in building its Natrium small modular reactor in the United Kingdom, the company announced.
TerraPower sent a letter to the U.K.’s Department for Energy Security and Net Zero, formally establishing its intention to enter the U.K. generic design assessment (GDA) process. This is TerraPower’s first step in deployment of its Natrium technology—a 345-MW sodium fast reactor coupled with a molten salt energy storage unit—on the international stage.
Roberto P. Domingos, Roberto Schirru, Cláudio M. N. A. Pereira
Nuclear Science and Engineering | Volume 152 | Number 2 | February 2006 | Pages 197-203
Technical Paper | doi.org/10.13182/NSE06-A2575
Articles are hosted by Taylor and Francis Online.
This work presents particle swarm optimization (PSO) as an alternative method for solving an optimization problem that arises during nuclear reactor core design. The method is introduced and applied to a simplified core optimization problem found in literature. When compared with other evolutionary computation-based methods, PSO performs better. Moreover, PSO presents easier modeling and demands less computational effort in the optimization process. The obtained results are shown and discussed.