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.
J. M. Martínez-Val, M. Piera, Y. Ronen
Nuclear Science and Engineering | Volume 105 | Number 4 | August 1990 | Pages 349-370
Technical Paper | doi.org/10.13182/NSE90-A21470
Articles are hosted by Taylor and Francis Online.
The discretized diffusion equation is structured in a formalism embodying in the left side all the terms involving the group fluxes at the generic point under calculation, and in the right side containing all the terms involving the fluxes at neighbor points. This formalism is especially suited for vectorial computation and also presents very good computing performance in scalar computers. The computing methodology includes an acceleration technique, “coarse-mesh precalculation,” to minimize computing times, particularly for cases with very large numbers of points. The algorithm is stable and positive, and it is improved by a discretization of the Laplacian operator using five points in each coordinate.