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
Aug 2026
Jan 2026
2026
Latest Journal Issues
Nuclear Science and Engineering
October 2026
Nuclear Technology
September 2026
Fusion Science and Technology
August 2026
Latest News
Front-end nuclear fuel supply cooperation: Turning allied interdependence into strategic advantage
The global nuclear revival, which is fueled by unprecedented demand for firm, affordable, dispatchable power for artificial intelligence and data center build-out, energy security imperatives, and climate commitments, has exposed a structural reality of the Western fuel cycle: No single allied nation currently possesses the full suite of front-end capabilities. From mining through conversion, enrichment, fabrication, and the emerging deconversion and metallization steps required for reactor fuels, capability is distributed across Canada, France, Japan, the United Kingdom, and the United States (collectively, the “Sapporo Five”), as well as a small group of close partners.
D. B. MacMillan
Nuclear Science and Engineering | Volume 39 | Number 3 | March 1970 | Pages 329-336
Technical Paper | doi.org/10.13182/NSE70-A19994
Articles are hosted by Taylor and Francis Online.
A mathematical method is described for the computation of the probability distribution of neutron populations in a point reactor with a weak source. The author and his colleagues have previously described a method for doing such computations, and G. I. Bell has described a different method; the present paper uses ideas from both of these older methods plus new formulations for computing the probability distribution from values of the generating function, for evaluating the probability distribution of precursor decay rates instead of that of neutron populations, and for evaluating the effect of short neutron lifetime without using unnecessarily short time steps in numerical integration. As a result, the method presented here is more widely applicable and more accurate than the older methods. The reactor model used here permits taking account of six delayed-neutron precursor groups and of finite neutron lifetime.