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
May 2026
Jan 2026
2026
Latest Journal Issues
Nuclear Science and Engineering
June 2026
Nuclear Technology
Fusion Science and Technology
Latest News
NRC proposes changes to its rules on nuclear materials
In response to Executive Order 14300, “Ordering the Reform of the Nuclear Regulatory Commission,” the NRC is proposing sweeping changes to its rules governing the use of nuclear materials that are widely used in industry, medicine, and research. The changes would amend NRC regulations for the licensing of nuclear byproduct material, some source material, and some special nuclear material.
As published in the May 18 Federal Register, the NRC is seeking public comment on this proposed rule and draft interim guidance until July 2.
Paul Wilson, Phiphat Phruksarojanakun
Nuclear Science and Engineering | Volume 152 | Number 3 | March 2006 | Pages 243-255
Technical Paper | doi.org/10.13182/NSE06-A2579
Articles are hosted by Taylor and Francis Online.
A new Monte Carlo (MC) method for calculating the isotopic inventory of material subjected to a neutron flux is developed and demonstrated. The method is particularly suited to modeling materials that flow through a system in a nondeterministic path. The method has strong analogies to MC neutral particle transport. The analog methodology is fully developed, including considerations for simple, complex, and loop flows, and enabling concepts such as sources and tallies. A wide variety of test problems is employed to demonstrate the validity of the analog method under various flow conditions. The method reproduced the results of the as-low-as-reasonably-achievable deterministic inventory code for comparable problems and is self-consistent when comparing complex flow scenarios to mathematically identical simple flow scenarios. A demonstration of highly scalable parallelization does not eliminate the need to develop variance reduction techniques.