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Division Spotlight
Young Members Group
The Young Members Group works to encourage and enable all young professional members to be actively involved in the efforts and endeavors of the Society at all levels (Professional Divisions, ANS Governance, Local Sections, etc.) as they transition from the role of a student to the role of a professional. It sponsors non-technical workshops and meetings that provide professional development and networking opportunities for young professionals, collaborates with other Divisions and Groups in developing technical and non-technical content for topical and national meetings, encourages its members to participate in the activities of the Groups and Divisions that are closely related to their professional interests as well as in their local sections, introduces young members to the rules and governance structure of the Society, and nominates young professionals for awards and leadership opportunities available to members.
Meeting Spotlight
2024 ANS Annual Conference
June 16–19, 2024
Las Vegas, NV|Mandalay Bay Resort and Casino
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
Proving DRACO will deliver
The United States is now closer than it has been in over five decades to launching the first nuclear thermal rocket into space, thanks to DRACO—the Demonstration Rocket for Agile Cislunar Orbit.
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.