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.
Explore membership for yourself or for your organization.
Conference Spotlight
2026 Nuclear Energy Conference & Expo (NECX)
August 24–27, 2026
Dallas, TX|Hilton Anatole
Latest Magazine Issues
Jun 2026
Jan 2026
2026
Latest Journal Issues
Nuclear Science and Engineering
July 2026
Nuclear Technology
Fusion Science and Technology
May 2026
Latest News
Breaking ground on a new approach to construction
The drive to Kairos Power’s reactor demonstration site in Oak Ridge, Tenn., is not only scenic—it’s historic. Nearly 85 years ago, roughly 30,000 construction workers transformed orchards and farmland into a key Manhattan Project site. Depending on your route, you may pass by one of the three gatehouses that were once military checkpoints controlling access to Atomic Energy Commission production facilities.
Ian Wall and Henri Fenech
Nuclear Science and Engineering | Volume 22 | Number 3 | July 1965 | Pages 285-297
Technical Paper | doi.org/10.13182/NSE65-A20933
Articles are hosted by Taylor and Francis Online.
The fuel management optimization of a nuclear power plant is separable from the over-all optimum design. It has weak interactions with the core design and poison management which may be expressed by constraints upon the maximum permissible fuel burnup and ratio of peak-to-average power density (power peaking). Each time the reactor becomes subcritical, a decision must be made as to which fuel should be discharged and replaced and to what degree rearrangement is advantageous. This is a multistage decision process whose objective is the minimum power cost over the plant life. A dynamic programing algorithm and a computer program have been developed to optimize the refueling policies of a single-enrichment, three-zone, 1000-MWe PWR core for a minimum unit power cost. The major assumptions necessary for this method are the representation of the fuel composition by the sole parameter, burnup, and the prediction of the system behavior by least-squares polynomial curves fitted to prior calculations. These approximations have been verified and their accuracy is about 3%. Many problems are displayed to demonstrate the application of the method. The cost figures given in the numerical examples are for illustration purposes only and may not reflect current manufacturers' and utilities' policies.