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
June 2026
Fusion Science and Technology
May 2026
Latest News
North American construction is back—smaller and faster—at OPG’s Darlington
“The nuclear renaissance is real here,” said Ontario Power Generation’s Subo Sinnathamby on May 8, one year to the day after OPG secured a final investment decision to build the first of four planned BWRX-300 reactors at its Darlington nuclear power plant, and shortly after the new reactor’s foundation was lifted into place. “We got our license to construct in April and our [final investment decision] in May, and we’ve been off to the races since.”
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.