ANS is committed to advancing, fostering, and promoting the development and application of nuclear sciences and technologies to benefit society.
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Division Spotlight
Education, Training & Workforce Development
The Education, Training & Workforce Development Division provides communication among the academic, industrial, and governmental communities through the exchange of views and information on matters related to education, training and workforce development in nuclear and radiological science, engineering, and technology. Industry leaders, education and training professionals, and interested students work together through Society-sponsored meetings and publications, to enrich their professional development, to educate the general public, and to advance nuclear and radiological science and engineering.
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.
Juan José Ortiz, Alejandro Castillo, José Luis Montes, Raúl Perusquía
Nuclear Science and Engineering | Volume 157 | Number 2 | October 2007 | Pages 236-244
Technical Note | doi.org/10.13182/NSE07-A2725
Articles are hosted by Taylor and Francis Online.
A new system to optimize both control rod pattern and fuel-loading design in boiling water reactors is shown. The system is named OCOTH, and it is based on heuristic techniques such as genetic algorithms, neural networks, and ant colonies. Each heuristic technique is used to design a part of the optimization process. So, the neural network finds an initial fuel loading with a Haling burnup calculation. The ant colony system optimizes full-power control rod pattern of the initial fuel loading. Finally, the genetic algorithm optimizes fuel loading with the optimized control rod patterns. The ant colony system and the genetic algorithm perform an iterative loop until a stop criterion is fulfilled; for example, control rod pattern and fuel-loading convergence. The OCOTH system was tested in an equilibrium cycle of Mexico's Laguna Verde Nuclear Power Plant. We found very good results in control rod pattern and fuel-loading coupled optimization.