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.
Thomas E. Booth, Edmond D. Cashwell
Nuclear Science and Engineering | Volume 71 | Number 2 | August 1979 | Pages 128-142
Technical Paper | doi.org/10.13182/NSE79-A20404
Articles are hosted by Taylor and Francis Online.
Equations are presented that allow the efficiencies of Monte Carlo techniques (for particle transport problems) to be calculated. This theory generalizes the theory of Amster and Djomehri to treat time-dependent multiplying systems, even when supercritical. Standard variance reducing techniques such as biased kernels, splitting, and Russian roulette are included in the theory. As concrete examples, the efficiencies of four Monte Carlo techniques for obtaining the expected number of collisions a particle makes have been analytically predicted. These predictions are stated and compared with the observed efficiencies obtained by Monte Carlo calculations using each of the four techniques.