ANS is committed to advancing, fostering, and promoting the development and application of nuclear sciences and technologies to benefit society.
Explore the many uses for nuclear science and its impact on energy, the environment, healthcare, food, and more.
Division Spotlight
Isotopes & Radiation
Members are devoted to applying nuclear science and engineering technologies involving isotopes, radiation applications, and associated equipment in scientific research, development, and industrial processes. Their interests lie primarily in education, industrial uses, biology, medicine, and health physics. Division committees include Analytical Applications of Isotopes and Radiation, Biology and Medicine, Radiation Applications, Radiation Sources and Detection, and Thermal Power Sources.
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!
Latest Magazine Issues
May 2024
Jan 2024
Latest Journal Issues
Nuclear Science and Engineering
June 2024
Nuclear Technology
Fusion Science and Technology
Latest News
Excelsior University student section awarded community education grant
The American Nuclear Society Student Section at Excelsior University in Albany, N.Y., was awarded a $5,000 grant from the ANS Student Section Strategic Fund initiative for its program, Empowering Tomorrow’s Nuclear Innovators: A Collaborative Approach to Nuclear Technology Education and Awareness.
Juan José Ortiz, Ignacio Requena
Nuclear Science and Engineering | Volume 146 | Number 1 | January 2004 | Pages 88-98
Technical Paper | doi.org/10.13182/NSE04-A2395
Articles are hosted by Taylor and Francis Online.
A genetic algorithm is used to optimize the nuclear fuel reload for a boiling water reactor, and an order coding is proposed for the chromosomes and appropriate crossover and mutation operators. The fitness function was designed so that the genetic algorithm creates fuel reloads that, on one hand, satisfy the constrictions for the radial power peaking factor, the minimum critical power ratio, and the maximum linear heat generation rate while optimizing the effective multiplication factor at the beginning and end of the cycle. To find the values of these variables, a neural network trained with the behavior of a reactor simulator was used to predict them. The computation time is therefore greatly decreased in the search process. We validated this method with data from five cycles of the Laguna Verde Nuclear Power Plant in Mexico.