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 ANS Annual Conference
May 31–June 3, 2026
Denver, CO|Sheraton Denver
Latest Magazine Issues
Jan 2026
Jul 2025
Latest Journal Issues
Nuclear Science and Engineering
February 2026
Nuclear Technology
January 2026
Fusion Science and Technology
November 2025
Latest News
Jeff Place on INPO’s strategy for industry growth
As executive vice president for industry strategy at the Institute of Nuclear Power Operations, Jeff Place leads INPO’s industry-facing work, engaging directly with chief nuclear officers.
Bo-In Lin, Burt Zolotar, Joel Weisman
Nuclear Technology | Volume 44 | Number 2 | July 1979 | Pages 258-275
Technical Paper | Fuel Cycle | doi.org/10.13182/NT79-A32260
Articles are hosted by Taylor and Francis Online.
An automated procedure determining a minimum cost refueling policy has been developed for light water reactors. The procedure is an extension of the equilibrium core approach previously devised for pressurized water reactors (PWRs). Use of group theory has improved the accuracy of the nuclear model and eliminated tedious fitting of albedos. A simple heuristic algorithm for locating a good starting policy has materially reduced PWR computing time. Inclusion of void effects and use of the Haling principle for axial flux calculations extended the nuclear model to boiling water reactors (BWRs). A good initial estimate of the refueling policy is obtained by recognizing that a nearly uniform distribution of reactivity provides low-power peaking. The initial estimate is improved upon by interchanging groups of four assemblies and is subsequently refined by interchanging individual assemblies. The method yields very favorable results, is simpler than previously proposed BWR fuel optimization schemes, and retains power cost as the objective function.