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
Nuclear Science and Engineering | Volume 154 | Number 1 | September 2006 | Pages 48-62
Technical Paper | doi.org/10.13182/NSE05-05
Articles are hosted by Taylor and Francis Online.
A method for simultaneously obtaining the two largest eigenvalues and their associated eigenfunctions is demonstrated mathematically and empirically. The method uses estimates of the eigenvalue in two different regions rather than the single estimate traditionally used. The method can be generalized to obtain the several largest eigenfunctions, if those are desired as well. Additionally, it is shown that using multiple estimates of the eigenvalues accelerates the convergence of the eigenfunctions.